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0

$begingroup$

I am referring to my previous question (Any suitable way to describe the distributions of 2 Pandas Dataframes visually/graphically?) related to visualising the Pandas dataframes to show that they have a similar distribution.

I have come to know that Kolmogorov–Smirnov test (K-S Test) can help decide whether the 2 distributions of dataframes are similar and how similar they are based on p-values etc. Based on the answer by Tasos in the referred question,

from scipy import stats
p_value = 0.05
rejected = 0
for col in df1:
 test = stats.ks_2samp(df1[col], df2[col])
 if test[1] < p_value:
 rejected += 1
print("We rejected",rejected,"columns in total")

It is possible to understand the context as to whether the distributions of the dataframes df1 and df2 are similar or not. However, I would like to present this information visually/graphically (such as Wikipedia have a graph for K-S test statistic: https://en.wikipedia.org/wiki/Kolmogorov–Smirnov_test). Any suggestions regarding a suitable method to visualise the K-S test statistical interpretation in Python would be highly appreciated. Cheers!

python pandas statistics dataframe descriptive-statistics

share|improve this question

asked Apr 1 at 20:57

JChatJChat

1378

$endgroup$

add a comment | 

0

$begingroup$

I am referring to my previous question (Any suitable way to describe the distributions of 2 Pandas Dataframes visually/graphically?) related to visualising the Pandas dataframes to show that they have a similar distribution.

I have come to know that Kolmogorov–Smirnov test (K-S Test) can help decide whether the 2 distributions of dataframes are similar and how similar they are based on p-values etc. Based on the answer by Tasos in the referred question,

from scipy import stats
p_value = 0.05
rejected = 0
for col in df1:
 test = stats.ks_2samp(df1[col], df2[col])
 if test[1] < p_value:
 rejected += 1
print("We rejected",rejected,"columns in total")

It is possible to understand the context as to whether the distributions of the dataframes df1 and df2 are similar or not. However, I would like to present this information visually/graphically (such as Wikipedia have a graph for K-S test statistic: https://en.wikipedia.org/wiki/Kolmogorov–Smirnov_test). Any suggestions regarding a suitable method to visualise the K-S test statistical interpretation in Python would be highly appreciated. Cheers!

python pandas statistics dataframe descriptive-statistics

share|improve this question

asked Apr 1 at 20:57

JChatJChat

1378

$endgroup$

add a comment | 

$begingroup$

I am referring to my previous question (Any suitable way to describe the distributions of 2 Pandas Dataframes visually/graphically?) related to visualising the Pandas dataframes to show that they have a similar distribution.

I have come to know that Kolmogorov–Smirnov test (K-S Test) can help decide whether the 2 distributions of dataframes are similar and how similar they are based on p-values etc. Based on the answer by Tasos in the referred question,

from scipy import stats
p_value = 0.05
rejected = 0
for col in df1:
 test = stats.ks_2samp(df1[col], df2[col])
 if test[1] < p_value:
 rejected += 1
print("We rejected",rejected,"columns in total")

It is possible to understand the context as to whether the distributions of the dataframes df1 and df2 are similar or not. However, I would like to present this information visually/graphically (such as Wikipedia have a graph for K-S test statistic: https://en.wikipedia.org/wiki/Kolmogorov–Smirnov_test). Any suggestions regarding a suitable method to visualise the K-S test statistical interpretation in Python would be highly appreciated. Cheers!

python pandas statistics dataframe descriptive-statistics

share|improve this question

asked Apr 1 at 20:57

JChatJChat

1378

$endgroup$

from scipy import stats
p_value = 0.05
rejected = 0
for col in df1:
 test = stats.ks_2samp(df1[col], df2[col])
 if test[1] < p_value:
 rejected += 1
print("We rejected",rejected,"columns in total")

share|improve this question

asked Apr 1 at 20:57

JChatJChat

1378

share|improve this question

asked Apr 1 at 20:57

JChatJChat

1378

asked Apr 1 at 20:57

JChatJChat

1378

asked Apr 1 at 20:57

JChatJChat

1378