Modeling Key considerations of the data:
Imbalanced outcome: Only 0.7% of parts actually go on backorder.
Outliers and skewed predictors: Part quantities (stock, sales etc.) can be on very different scales.
Missing data: A few variables have data that are missing (not at random).
n>>p: There are many observations (1.9 million) relative to the number of predictors (22).
Implemented Models
We made several modeling decisions to address these issues:
Random forest estimators are used
Perform well with imbalanced data typically
Robust to outliers and the skewed predictors: Because they are using tree partitioning algorithms and not producing coefficient estimates, outliers and skewness are not as much of a concern as for other predictive models.
Down sampling: to account for the imbalanced outcome, we try down sampling the data of parts that didn't go on backorder.
We choose down sampling over other similar methods that resample the minority group (e.g. up sampling or SMOTE) as these are more computationally burdensome with a large sample size.
Dealing with missing data: The few variables with missing data had medians imputed, and a binary variable was created to indicate whether the observation had missing data, in hopes to account for the missing data not being random.
Validation
We use 10-fold cross-validation in order to tune model parameters (maximum number of variables to try and minimum leaf size), as well as compare model performance.
The ROC Area Under the Curve (AUC) was used as a validation metric because the outcome is so imbalanced. By looking at ROC curves, we may determine a cutoff threshold for classification after fitting the models, rather than naively assuming a threshold of 0.5.
import csv
import numpy as np
import pandas as pd
import os
import matplotlib.pyplot as plt
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import KFold
from sklearn.utils import resample
from sklearn.metrics import roc_curve, roc_auc_score, precision_recall_curve, confusion_matrix, accuracy_score
#----------Import and view the data-----------#
#Set working directory
#Import both datasets
# a = pd.read_csv("Kaggle_Training_Dataset_v2.csv")
# b = pd.read_csv("Kaggle_Test_Dataset_v2.csv")
#Combine into one dataset
#merged = pd.concat([a,b])
merged = pd.read_csv("data/backorder.csv")
#first 5 entries
merged.head(5).transpose()
#---------- Basic Data Manipulation-----------#
#recode binary variables as 0 / 1 rather than No / Yes
for col in ['potential_issue',
'deck_risk',
'oe_constraint',
'ppap_risk',
'stop_auto_buy',
'rev_stop',
'went_on_backorder']:
merged[col]=pd.factorize(merged[col])[0]
#remove the two rows of all NA's
merged=merged[pd.notnull(merged['national_inv'])]
#Change the -99 placeholder to NA for perf_6_month_avg and perf_12_month_avg
merged['perf_6_month_avg']=merged['perf_6_month_avg'].replace(-99, np.NaN)
merged['perf_12_month_avg']=merged['perf_12_month_avg'].replace(-99, np.NaN)
#define quantitative and categorical variable lists
quantvars=['national_inv',
'lead_time',
'in_transit_qty',
'forecast_3_month',
'forecast_6_month',
'forecast_9_month',
'sales_1_month',
'sales_3_month',
'sales_6_month',
'sales_9_month',
'min_bank',
'pieces_past_due',
'perf_6_month_avg',
'perf_12_month_avg',
'local_bo_qty']
catvars=['potential_issue',
'deck_risk',
'oe_constraint',
'ppap_risk',
'stop_auto_buy',
'rev_stop',
'went_on_backorder']
catpred=['potential_issue',
'deck_risk',
'oe_constraint',
'ppap_risk',
'stop_auto_buy',
'rev_stop']
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2728: DtypeWarning: Columns (0) have mixed types. Specify dtype option on import or set low_memory=False.
interactivity=interactivity, compiler=compiler, result=result)
Descriptive Statistics and Plots
I considered descriptive statistics and plots for the variables in the dataset. Some of the descriptive findings are:
Several predictors are skewed or have huge outliers
Part quantities (stock, sales etc.) can be on very different scales
Descriptively, backordered parts are on average associated with:
lower inventory
lower sales forecasts
worse sales history
more frequent potential risk flags
Several predictors are highly correlated
Especially the sales and forecast variables which are related and have overlap (e.g. 3 month sales history and 6 month sales history)
merged[quantvars].describe().transpose()
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| national_inv | 242075.0 | 499.751028 | 29280.390793 | -25414.0 | 4.00 | 15.00 | 81.00 | 12145792.0 |
| lead_time | 227351.0 | 7.923018 | 7.041410 | 0.0 | 4.00 | 8.00 | 9.00 | 52.0 |
| in_transit_qty | 242075.0 | 36.178213 | 898.673127 | 0.0 | 0.00 | 0.00 | 0.00 | 265272.0 |
| forecast_3_month | 242075.0 | 181.472345 | 5648.874620 | 0.0 | 0.00 | 0.00 | 4.00 | 1510592.0 |
| forecast_6_month | 242075.0 | 348.807304 | 10081.797119 | 0.0 | 0.00 | 0.00 | 12.00 | 2157024.0 |
| forecast_9_month | 242075.0 | 508.296301 | 14109.723787 | 0.0 | 0.00 | 0.00 | 20.00 | 3162260.0 |
| sales_1_month | 242075.0 | 51.478195 | 1544.678350 | 0.0 | 0.00 | 0.00 | 4.00 | 349620.0 |
| sales_3_month | 242075.0 | 172.139316 | 5164.243624 | 0.0 | 0.00 | 1.00 | 14.00 | 1099852.0 |
| sales_6_month | 242075.0 | 340.425414 | 9386.523492 | 0.0 | 0.00 | 2.00 | 30.00 | 2103389.0 |
| sales_9_month | 242075.0 | 511.775446 | 13976.702192 | 0.0 | 0.00 | 4.00 | 46.00 | 3195211.0 |
| min_bank | 242075.0 | 52.804693 | 1278.591177 | 0.0 | 0.00 | 0.00 | 3.00 | 303713.0 |
| pieces_past_due | 242075.0 | 1.824236 | 178.679263 | 0.0 | 0.00 | 0.00 | 0.00 | 79964.0 |
| perf_6_month_avg | 222974.0 | 0.779340 | 0.239060 | 0.0 | 0.70 | 0.85 | 0.97 | 1.0 |
| perf_12_month_avg | 224100.0 | 0.776331 | 0.232118 | 0.0 | 0.69 | 0.83 | 0.96 | 1.0 |
| local_bo_qty | 242075.0 | 0.843726 | 45.606626 | 0.0 | 0.00 | 0.00 | 0.00 | 6232.0 |
#---Quantitative variables-----#
#summary of quantitative variables
merged[quantvars].describe().transpose()
#means by backorder status
merged.pivot_table(values=quantvars,index=['went_on_backorder'])
# #boxplots of quantitative variables //Uncomment to see outliers
# for col in quantvars:
# print(col)
# plt.boxplot(merged[col])
# plt.show()
#---Categorical variables-----#
#Percentage of each categorical variable
print("percentage missing")
print("____________________")
for col in catvars:
print(col,": ",round(merged[col].mean()*100,2),"%" )
#Proportions of categorical predictors stratified by went_on_backorder
merged.pivot_table(values=(catpred),index=["went_on_backorder"])
#barplots of proportions stratified by went_on_backorder
for col in catpred:
noback=np.array(merged.pivot_table(values=(col),index=["went_on_backorder"]))[0]
yesback=np.array(merged.pivot_table(values=(col),index=["went_on_backorder"]))[1]
names = ('Not Backordered', 'Backordered')
y_pos = np.arange(2)
proportions = [noback,yesback]
plt.bar(y_pos, proportions, align='center', alpha=0.5)
plt.xticks(y_pos, names)
plt.ylabel('proportion')
plt.title("Proportion of %s by backorder status" % (col))
plt.show()
# Correction Matrix Plot of all variables
varnames=list(merged)[1:]
correlations = merged[varnames].corr()
fig = plt.figure()
ax = fig.add_subplot(111)
cax = ax.matshow(correlations, vmin=-1, vmax=1)
fig.colorbar(cax)
ticks = np.arange(0,23,1)
ax.set_xticks(ticks)
ax.set_yticks(ticks)
ax.set_xticklabels(varnames,rotation=90)
ax.set_yticklabels(varnames)
plt.show()
percentage missing
____________________
potential_issue : 0.03 %
deck_risk : 80.18 %
oe_constraint : 0.02 %
ppap_risk : 11.86 %
stop_auto_buy : 3.91 %
rev_stop : 0.04 %
went_on_backorder : 1.11 %
Dealing with Missing Data
Three predictors have missing data:
lead_time (6% missing)
perf_6_month_avg (7.7% missing)
perf_12_month_avg (7.3% missing)
From comparing descriptive statistics of the complete dataset to the data with missing values, we find that the data is clearly not missing at random. For these three variables, we impute the medians for the missing observations. We also create an indicator variable for whether any variable was missing, in hope to help account for the non-randomness of the missing data.
Missing not at Random (MNAR): Two possible reasons are that the missing value depends on the hypothetical value (e.g. People with high salaries generally do not want to reveal their incomes in surveys) or missing value is dependent on some other variable’s value (e.g. Let’s assume that females generally don’t want to reveal their ages! Here the missing value in age variable is impacted by gender variable). With missing at random, it is safe to remove the rows (MAR), with MNAR, you would induce bias if you remove the rows. Whether or not it is random you can impute it. If it is MNAR you can impute the median/mean as you would for MAR, but you can also create an extra column to express the fat that the value was missing, as this might carry some information.
#View count/percentage of missing cells
tot=merged.isnull().sum().sort_values(ascending=False)
perc=(round(100*merged.isnull().sum()/merged.isnull().count(),1)).sort_values(ascending=False)
missing_data = pd.concat([tot, perc], axis=1, keys=['Missing', 'Percent'])
missing_data
| Missing | Percent | |
|---|---|---|
| perf_6_month_avg | 19101 | 7.9 |
| perf_12_month_avg | 17975 | 7.4 |
| lead_time | 14724 | 6.1 |
| went_on_backorder | 0 | 0.0 |
| sales_6_month | 0 | 0.0 |
| national_inv | 0 | 0.0 |
| in_transit_qty | 0 | 0.0 |
| forecast_3_month | 0 | 0.0 |
| forecast_6_month | 0 | 0.0 |
| forecast_9_month | 0 | 0.0 |
| sales_1_month | 0 | 0.0 |
| sales_3_month | 0 | 0.0 |
| min_bank | 0 | 0.0 |
| sales_9_month | 0 | 0.0 |
| rev_stop | 0 | 0.0 |
| potential_issue | 0 | 0.0 |
| pieces_past_due | 0 | 0.0 |
| local_bo_qty | 0 | 0.0 |
| deck_risk | 0 | 0.0 |
| oe_constraint | 0 | 0.0 |
| ppap_risk | 0 | 0.0 |
| stop_auto_buy | 0 | 0.0 |
| sku | 0 | 0.0 |
#create a variable for any missing data
merged['anymissing']=( pd.isnull(merged['perf_6_month_avg'] ) |
pd.isnull(merged['perf_12_month_avg'] ) |
pd.isnull(merged['lead_time'] ) ).astype(int)
'''
Compare complete data to data with any missing variables
> Means of quantitative variables
> Proportions of categorical variables
'''
##This allows you to see that the values are not missing at random.
merged.pivot_table(values=(quantvars),index=['anymissing'])
| forecast_3_month | forecast_6_month | forecast_9_month | in_transit_qty | lead_time | local_bo_qty | min_bank | national_inv | perf_12_month_avg | perf_6_month_avg | pieces_past_due | sales_1_month | sales_3_month | sales_6_month | sales_9_month | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| anymissing | |||||||||||||||
| 0 | 194.621247 | 373.299685 | 543.712796 | 36.747240 | 7.831527 | 0.877107 | 51.480635 | 369.933468 | 0.777906 | 0.77934 | 1.951344 | 51.434042 | 172.885525 | 345.178523 | 521.716016 |
| 1 | 27.979687 | 62.897440 | 94.864667 | 29.535731 | 12.583733 | 0.454060 | 68.260981 | 2015.165960 | 0.464449 | NaN | 0.340453 | 51.993613 | 163.428512 | 284.940370 | 395.734988 |
merged.pivot_table(values=(catvars),index=['anymissing'])
| deck_risk | oe_constraint | potential_issue | ppap_risk | rev_stop | stop_auto_buy | went_on_backorder | |
|---|---|---|---|---|---|---|---|
| anymissing | |||||||
| 0 | 0.832164 | 0.000211 | 0.000363 | 0.114910 | 0.000238 | 0.025819 | 0.011499 |
| 1 | 0.447830 | 0.000000 | 0.000052 | 0.162086 | 0.002879 | 0.193759 | 0.006492 |
#impute the medians
merged=merged.fillna(merged.median())
#create a blank dataframe to fill
merged_pred=pd.DataFrame(data=None,index=merged.index)
#Define folds for 10-fold Cross Validation
kf = KFold(n_splits=10,shuffle=True,random_state=123)
#Define index of dataset (to help in data sepparations within folds)
ind=merged.index
#----------fit models and product predictions in each fold----------#
for train_index, test_index in kf.split(merged):
#Define Training data
merged_train=merged[ind.isin(train_index)]
y_train=merged_train['went_on_backorder']
X_train=merged_train.drop(['sku','went_on_backorder'],axis=1)
#Define Test data
merged_test=merged[ind.isin(test_index)]
y_test=merged_test['went_on_backorder']
X_test=merged_test.drop(['sku','went_on_backorder'],axis=1)
#Define down-sampled training data
train_majority = merged_train[y_train==0]
train_minority = merged_train[y_train==1]
n_minority = len(train_minority)
train_majority_downsampled = resample(train_majority,
replace=False,
n_samples=n_minority,
random_state=123)
train_downsampled = pd.concat([train_majority_downsampled, train_minority])
y_train_downsampled = train_downsampled['went_on_backorder']
X_train_downsampled = train_downsampled.drop(['sku','went_on_backorder'],axis=1)
#---------------------------------------------------------------#
#Function to fit models
def fitrandomforests(n_est,maxfeat,minleaf):
#names of model predictions based on tuning parameter inputs
varname= "pred_nest%s_feat%s_leaf%s" % (n_est,maxfeat,minleaf)
varname2= "pred_down_nest%s_feat%s_leaf%s" % (n_est,maxfeat,minleaf)
#Fit a Random Forest model
rf=RandomForestClassifier(n_estimators=n_est,
max_features=maxfeat,
min_samples_leaf=minleaf)
rf.fit(X_train,y_train)
preds=rf.predict_proba(X_test)[:,1]
merged_test[varname]=preds
#Fit a Random Forest model on downsampled data
rfd=RandomForestClassifier(n_estimators=n_est,
max_features=maxfeat,
min_samples_leaf=minleaf)
rfd.fit(X_train_downsampled,y_train_downsampled)
predsd=rfd.predict_proba(X_test)[:,1]
merged_test[varname2]=predsd
#---------------------------------------------------------------#
#Tuning parameter grids
#number of trees (more is better for prediction but slower)
n_est=50
#maximum features tried
maxfeatgrid=[3,5,7]
#Minimum samples per leaf
minleafgrid=[5,10,30]
#fit models
for feat in maxfeatgrid:
for leaf in minleafgrid:
fitrandomforests(n_est,feat,leaf)
#Combine predictions for this fold with previous folds
merged_pred = pd.concat([merged_pred,merged_test])
#drop NA's from dataframe caused by the method for combining datasets from each loop iteration
merged_pred=merged_pred.dropna()
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A value is trying to be set on a copy of a slice from a DataFrame.
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/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:51: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:59: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
#View AUC for each model and each tuning parameter specification
for feat in maxfeatgrid:
for leaf in minleafgrid:
#Random forest for given tuning parameters
varname1="pred_nest50_feat%s_leaf%s" % (feat,leaf)
rocscore1=roc_auc_score(merged_pred['went_on_backorder'],merged_pred[varname1])
print( round(rocscore1,4 ) , varname1 )
#Down Sampled Random Forest for given tuning parameters
varname2="pred_down_nest50_feat%s_leaf%s" % (feat,leaf)
rocscore2=roc_auc_score(merged_pred['went_on_backorder'],merged_pred[varname2])
print( round(rocscore2,4) , varname2 )
#ROC Curves for top performing models
#Define false positive rates/true positive rates / thresholds
#Best random forest model
fpr, tpr, thresholds = roc_curve(merged_pred['went_on_backorder'],
merged_pred['pred_nest50_feat3_leaf5'])
#Best down sampled random forest model
fpr2, tpr2, thresholds2 = roc_curve(merged_pred['went_on_backorder'],
merged_pred['pred_down_nest50_feat7_leaf5'])
#AUC for best Random Forest and Random Forest Down sampled Models
roc_auc=roc_auc_score(merged_pred['went_on_backorder'],
merged_pred['pred_nest50_feat3_leaf5'])
roc_auc2=roc_auc_score(merged_pred['went_on_backorder'],
merged_pred['pred_down_nest50_feat7_leaf5'])
%matplotlib inline
#plot ROC Curve
plt.title('ROC Curve')
plt.plot(fpr, tpr, 'b', label='RF (AUC = %0.3f)'% roc_auc)
plt.plot(fpr2, tpr2, 'g', label='RF Downsampled (AUC = %0.3f)'% roc_auc2)
plt.plot([0,1],[0,1],'r--', label='Random Guess')
plt.legend(loc='lower right')
plt.xlim([0,1])
plt.ylim([0,1])
(0, 1)
merged_pred.head()
| anymissing | deck_risk | forecast_3_month | forecast_6_month | forecast_9_month | in_transit_qty | lead_time | local_bo_qty | min_bank | national_inv | ... | pred_nest50_feat7_leaf30 | pred_nest50_feat7_leaf5 | rev_stop | sales_1_month | sales_3_month | sales_6_month | sales_9_month | sku | stop_auto_buy | went_on_backorder | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 9 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 8.0 | 0.0 | 0.0 | 2.0 | ... | 0.001133 | 0.000186 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3286325 | 0.0 | 0.0 |
| 21 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 8.0 | 0.0 | 2.0 | 265.0 | ... | 0.000000 | 0.000000 | 0.0 | 2.0 | 14.0 | 29.0 | 46.0 | 3289088 | 0.0 | 0.0 |
| 22 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 8.0 | 0.0 | 0.0 | 5.0 | ... | 0.000028 | 0.000010 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3289182 | 0.0 | 0.0 |
| 33 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 8.0 | 0.0 | 0.0 | 5.0 | ... | 0.000618 | 0.000460 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 3291956 | 0.0 | 0.0 |
| 35 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 8.0 | 0.0 | 0.0 | 16.0 | ... | 0.000431 | 0.000020 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3292280 | 0.0 | 0.0 |
5 rows × 42 columns
merged_pred["lead_time"].mean()
7.9277000929464005
merged_pred["forecast_9_month"].max()/
3162260.0
merged_pred["revenue"] = 300 + 200*(merged_pred["forecast_9_month"]/100)
merged_pred["revenue"] =merged_pred["revenue"].apply(lambda x: 1000 if x>1000 else x)
merged_pred["cost"] = -2 - merged_pred["lead_time"] - merged_pred["revenue"]*.07
merged_pred["cost"].hist()
<matplotlib.axes._subplots.AxesSubplot at 0x1a29603ac8>
# merged_pred["revenue"].mean()
b = 0.05
frame = pd.DataFrame(index=list(range(100)))
frame["threshold"] = 0
frame["tpr"] = 0
frame["fpr"] = 0
frame["fnr"] = 0
frame["tnr"] = 0
frame["tpr"] = 0
frame["fpr"] = 0
frame["fnr"] = 0
frame["tnr"] = 0
frame["cb_tn"] = 0
frame["cb_tp"] = 0
frame["cb_fp"] = 0
frame["cb_fn"] = 0
for i, b in enumerate(np.arange(0.0, 1.01, 0.01)):
print(i, b)
merged_pred["new_pred"] = merged_pred['pred_down_nest50_feat7_leaf5'].apply(lambda x: 1 if x< (1-b) else 0)
print(len(merged_pred[merged_pred["new_pred"]==1]))
profit = merged_pred[merged_pred["new_pred"]==1]["revenue"].mean()
cost = merged_pred[merged_pred["new_pred"]==1]["cost"].mean()
print(profit,cost)
confusion_mat = confusion_matrix(merged_pred['went_on_backorder'],merged_pred["new_pred"])
TN = confusion_mat[0][0]
FP = confusion_mat[0][1]
TP = confusion_mat[1][1]
FN = confusion_mat[1][0]
frame.loc[i, "TN"] = TN
frame.loc[i, "FP"] = FP
frame.loc[i, "TP"] = TP
frame.loc[i, "FN"] = FN
TPR = TP/(TP+FN)
# Specificity or true negative rate
TNR = TN/(TN+FP)
# Precision or positive predictive value
PPV = TP/(TP+FP)
# Negative predictive value
NPV = TN/(TN+FN)
# Fall out or false positive rate
FPR = FP/(FP+TN)
# False negative rate
FNR = FN/(TP+FN)
# False discovery rate
FDR = FP/(TP+FP)
frame.loc[i, "threshold"] = 1-b
frame.loc[i, "tpr"] = TPR
frame.loc[i, "fpr"] = FPR
frame.loc[i, "fnr"] = FNR
frame.loc[i, "tnr"] = TNR
## binary it only makes sense one way
frame.loc[i, "cb_tn"] = 0
frame.loc[i, "cb_tp"] = profit
frame.loc[i, "cb_fp"] = cost
frame.loc[i, "cb_fn"] = 0
0 0.0
242031
399.15619899930175 -37.86874483020615
1 0.01
241780
399.0956241211018 -37.865256845064216
2 0.02
241346
399.0153224002055 -37.86120606929315
3 0.03
240832
398.9169711666224 -37.856240200636265
4 0.04
240223
398.82198623778737 -37.853132214649015
5 0.05
239603
398.7245151354532 -37.84938544175005
6 0.06
238928
398.6396236523137 -37.84711193330056
7 0.07
238227
398.5436579396962 -37.844409743646345
8 0.08
237621
398.4741836790519 -37.843037357807745
9 0.09
236896
398.43305923274346 -37.84478783938796
10 0.1
236221
398.3576650678813 -37.843520347469706
11 0.11
235551
398.3066597042679 -37.844463576888494
12 0.12
234821
398.2213430655691 -37.844176542982396
13 0.13
234113
398.1799985477099 -37.84632198980693
14 0.14
233409
398.1314859324191 -37.84840361768257
15 0.15
232767
398.1287467725236 -37.8526783435783
16 0.16
232100
398.100215424386 -37.85650236966697
17 0.17
231461
398.1000341310199 -37.86209443491433
18 0.18
230753
398.0919858030015 -37.867448743893746
19 0.19
230083
398.1046752693593 -37.87409873828014
20 0.2
229446
398.0692973510107 -37.87601684056251
21 0.21
228779
398.06824052906956 -37.881325558725734
22 0.22
228073
398.0654439587325 -37.88696426144137
23 0.23
227341
398.08170985435976 -37.89498409877548
24 0.24
226637
398.0685060250533 -37.89990442866657
25 0.25
225960
398.05481501150643 -37.904384050272974
26 0.26
225236
398.0443889964304 -37.90776261343515
27 0.27
224504
398.0479456936179 -37.91346221002597
28 0.28
223750
398.016938547486 -37.91746279329458
29 0.29
222997
398.0090763552873 -37.92242989815853
30 0.3
222243
398.02110302686697 -37.92924087597653
31 0.31
221479
398.02437251387266 -37.93471525516944
32 0.32
220733
397.9843521358383 -37.938317333609746
33 0.33
219937
397.9807854067301 -37.94419310984364
34 0.34
219156
397.9707788059647 -37.949670006751774
35 0.35000000000000003
218400
397.96753663003665 -37.95557554944917
36 0.36
217636
397.9429689941002 -37.959612012717145
37 0.37
216856
397.8789795993655 -37.96160622717244
38 0.38
216047
397.8627520863516 -37.96627946696649
39 0.39
215245
397.76565309298707 -37.96558228994737
40 0.4
214405
397.7067325855274 -37.96811100487264
41 0.41000000000000003
213573
397.6575316168242 -37.971175382654714
42 0.42
212690
397.60585829141 -37.974212703934
43 0.43
211765
397.53983897244586 -37.97678407668755
44 0.44
210867
397.47370617498234 -37.9788073050774
45 0.45
209995
397.40303340555727 -37.98129241172298
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209069
397.305530709957 -37.98178543925581
47 0.47000000000000003
208091
397.2147185606297 -37.98260165023849
48 0.48
207135
397.08231829483185 -37.9807382624848
49 0.49
206149
396.9539507831714 -37.979894154227274
50 0.5
205140
396.8283903675539 -37.9785332943346
51 0.51
204018
396.63626738817163 -37.97353498220649
52 0.52
202930
396.5445030306017 -37.97354417779441
53 0.53
201777
396.42287277539066 -37.9752363252493
54 0.54
200676
396.25446989176584 -37.9733368215424
55 0.55
199527
396.0874067168854 -37.9705465425724
56 0.56
198246
395.86526840390223 -37.96467732009649
57 0.5700000000000001
196999
395.5723937684963 -37.95327194554215
58 0.58
195761
395.3174534253503 -37.944931830139126
59 0.59
194250
395.1457503217503 -37.94503135135067
60 0.6
192684
394.91780324261487 -37.94014521184885
61 0.61
191214
394.64273536456534 -37.9335358289659
62 0.62
189762
394.3427662018739 -37.923066999714955
63 0.63
188334
394.00904775558314 -37.91243216838124
64 0.64
186919
393.6291013754621 -37.898330613794776
65 0.65
185236
393.34627178302276 -37.88985024509229
66 0.66
183663
392.8452872924868 -37.86826459330361
67 0.67
181966
392.31495993757073 -37.84518470483468
68 0.68
180310
391.7078697798236 -37.81631756419475
69 0.6900000000000001
178526
391.2984887355343 -37.80473309209843
70 0.7000000000000001
176828
390.6878774854661 -37.77839437193185
71 0.71
174962
390.0373109589511 -37.75209794126709
72 0.72
173210
389.29230413948386 -37.71509381675413
73 0.73
171302
388.5360707989399 -37.67979603273742
74 0.74
169306
387.6483763127119 -37.636449505628775
75 0.75
167257
386.5973083338814 -37.58343997560634
76 0.76
165108
385.55056084502263 -37.53182002083484
77 0.77
162823
384.5810112821899 -37.48930052879507
78 0.78
160476
383.38072982875946 -37.42958710336741
79 0.79
157971
382.05508606009965 -37.36500167752311
80 0.8
155305
380.65509803290297 -37.29570715688489
81 0.81
152505
379.2226746664044 -37.22681735025084
82 0.8200000000000001
149522
377.7655729591632 -37.15880258423512
83 0.8300000000000001
146439
376.0593830878386 -37.070788519451874
84 0.84
143174
374.19583164541046 -36.979577157863936
85 0.85
139427
372.238103093375 -36.88908848357936
86 0.86
135478
370.04484861010644 -36.7754212492067
87 0.87
131080
367.5987030820873 -36.648517393957974
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126246
365.1629516974795 -36.53675633287396
89 0.89
121168
362.26416215502445 -36.398939323913936
90 0.9
115437
359.19329157895646 -36.26039935202752
91 0.91
109274
355.91295276094957 -36.10149935025712
92 0.92
102366
352.4817810601176 -35.94389250337026
93 0.93
94436
349.05245880808167 -35.77177411156762
94 0.9400000000000001
85675
344.63063904289464 -35.54055558797773
95 0.9500000000000001
75804
339.5082317555802 -35.28057543137553
96 0.96
64419
334.19888542200283 -34.98154364395598
97 0.97
52166
327.9042288080359 -34.61456964306261
98 0.98
36830
321.815313603041 -34.19706923703506
99 0.99
19557
314.7107429564862 -33.82404561026743
100 1.0
0
nan nan
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:45: RuntimeWarning: invalid value encountered in long_scalars
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py:53: RuntimeWarning: invalid value encountered in long_scalars
frame.head()
| threshold | tpr | fpr | fnr | tnr | cb_tn | cb_tp | cb_fp | cb_fn | TN | FP | TP | FN | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1.00 | 0.990327 | 0.999925 | 0.009673 | 0.000075 | 0.0 | 399.156199 | -37.868745 | 0.0 | 18.0 | 239369.0 | 2662.0 | 26.0 |
| 1 | 0.99 | 0.959077 | 0.999227 | 0.040923 | 0.000773 | 0.0 | 399.095624 | -37.865257 | 0.0 | 185.0 | 239202.0 | 2578.0 | 110.0 |
| 2 | 0.98 | 0.909598 | 0.997970 | 0.090402 | 0.002030 | 0.0 | 399.015322 | -37.861206 | 0.0 | 486.0 | 238901.0 | 2445.0 | 243.0 |
| 3 | 0.97 | 0.852679 | 0.996462 | 0.147321 | 0.003538 | 0.0 | 398.916971 | -37.856240 | 0.0 | 847.0 | 238540.0 | 2292.0 | 396.0 |
| 4 | 0.96 | 0.803943 | 0.994465 | 0.196057 | 0.005535 | 0.0 | 398.821986 | -37.853132 | 0.0 | 1325.0 | 238062.0 | 2161.0 | 527.0 |
# frame["cb_tp"] = 300
# frame["cb_fp"] = -40
frame["p"] = 1 - frame["threshold"]
frame["exp_val"] = frame["p"]*(frame["tpr"]*frame["cb_tp"] + frame["fnr"]*frame["cb_fn"]) + frame["threshold"]*(frame["tnr"]*frame["cb_tn"] + frame["fpr"]*frame["cb_fp"])
## So the best cutoff is around 50
## With a balanced dataset better threshold estimation
## This woud change depending on the moddel used.
frame[["threshold","exp_val"]].plot()
<matplotlib.axes._subplots.AxesSubplot at 0x1a1d4a9e48>
#you can maybe work direclty with precision and recall to creat what you wan tot.a
#define precision, recall, and corresponding threshold for model with highest AUC
precision, recall, threshold = precision_recall_curve(merged_pred['went_on_backorder'],
merged_pred['pred_down_nest50_feat7_leaf5'])
#plot Precision and Recall for a given threshold.
plt.title('Precision and Recall')
plt.plot(threshold,precision[1:],'purple',label='Precision')
plt.plot(threshold,recall[1:],'orange', label='Recall')
plt.axvline(x=.05,linestyle=":")
plt.legend(loc=2,bbox_to_anchor=(1.05, 1))
plt.xlim([0,1])
plt.ylim([0,1])
plt.ylabel('Precision and Recall Values')
plt.xlabel('Threshold')
<matplotlib.text.Text at 0x1a25fff668>
