Breaking News: Grepper is joining You.com. Read the official announcement!

pandas summary statistics by group

Athul Mathew answered on August 18, 2022 Popularity 3/10 Helpfulness 1/10

answer pandas summary statistics by group

pandas summary statistics by group

Comment

# generate base summary df using pd describe() function.
summary_df = Df.describe()

# dict intitialisation.
myu_sigma_dict = dict()
myupsigma_dict = dict()
outlier_dict = dict()
outlier_pct_dict = dict()

# index column defenition.
myu_sigma_dict["index"] = "µ-3σ"
myupsigma_dict["index"] = "µ+3σ"
outlier_dict["index"] = "outlier count"
outlier_pct_dict["index"] = "outlier(%)"
for col in summary_df.columns:
    myu = summary_df[col]["mean"]
    sigma = summary_df[col]["std"]
    myu_sigma_dict[col] = (myu - 3*sigma)
    myupsigma_dict[col] = (myu + 3*sigma)
    outlier_dict[col] = Df[(Df[col] < (myu - 3*sigma)) | (Df[col] > (myu + 3*sigma))].shape[0]
    outlier_pct_dict[col] = outlier_dict[col]*100/summary_df[col]["count"]

# add the newly created metrics to summary df.
summary_df = summary_df.reset_index()
summary_df = summary_df.append( myu_sigma_dict , ignore_index=True)
summary_df = summary_df.append( myupsigma_dict , ignore_index=True)
summary_df = summary_df.append( outlier_dict, ignore_index=True)
summary_df = summary_df.append( outlier_pct_dict, ignore_index=True)

display(summary_df)

Popularity 3/10 Helpfulness 1/10 Language python

Source: Grepper

Tags: group pandas python statistics summary

Link to this answer
Share Copy Link

Contributed on Aug 18 2022

Athul Mathew

0 Answers Avg Quality 2/10

pandas summary statistics by group

Contents

More Related Answers

pandas summary statistics by group

Grepper

Documentation

Social

Legal

Contact

Oops, You will need to install Grepper and log-in to perform this action.