Buildlytics

A comprehensive way to make your Exploratory data analysis process easy by using our package

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Preview

• Preview of our package

Functionalities

The module contains DataFrameSummary function which takes dataframe in its parameter

• properties
  • dfs.columns_stats: counts, uniques, missing, missing_perc, and type per column etc.
  • dsf.columns_types: a count of the types of columns
  • dfs[column]: more in depth summary of the column

Instructions to run

• Pre-requisites:

  • Install Pandas, Seaborn, Matplotlib
  • Install Python

The module can be easily installed with pip:

!pip3 install buildlytics --upgrade

The DataFrameSummary expect a pandas DataFrame to summarise.

from pandas_summary import DataFrameSummary

dfs = DataFrameSummary(tips)

To get the columns types

dfs.columns_types


bool           3
numeric        3
categorical    1
Name: types, dtype: int64

To get the overall columns stats

dfs.columns_stats

	total_bill	tip	sex	smoker	day	time	size
counts	244	244	244	244	244	244	244
uniques	229	123	2	2	4	2	6
missing	0	0	0	0	0	0	0
missing_perc	0%	0%	0%	0%	0%	0%	0%
types	numeric	numeric	bool	bool	categorical	bool	numeric

To get the particular column stats

dfs['total_bill']

mean                            19.7859
std                             8.90241
variance                        79.2529
min                                3.07
max                               50.81
mode                              13.42
5%                               9.5575
25%                             13.3475
50%                              17.795
75%                             24.1275
95%                              38.061
iqr                               10.78
kurtosis                        1.21848
skewness                        1.13321
sum                             4827.77
mad                             6.86944
cv                             0.449936
zeros_num                             0
zeros_perc                           0%
deviating_of_mean                     4
deviating_of_mean_perc            1.64%
deviating_of_median                  12
deviating_of_median_perc          4.92%
top_correlations            tip: 67.57%
counts                              244
uniques                             229
missing                               0
missing_perc                         0%
types                           numeric
Name: total_bill, dtype: object

To get the heatmap

dfs._get_heatmap(tips) //tips is the dataframe

To get the pairplot

pairplot=DataFrameSummary(tips)
pairplot._get_pairplot()

To get the scatterplot

dfs._get_scatterplot(tips['total_bill'],tips['tip'],tips['day'])

Contribute to this package

For Maintainers:

Guide for adding new features:

• You need to download the zip file for this project

• Download the package : buildlytics using pip3

• Whatever changes you make to the code will only be reflected if package is updated with your changes, so, incase you are not the maintainer on PyPi , drop a message in the discord group.

• Update the version before uploading in setup.py

For uploading version changes type the following in terminal of the downloaded folder :

python3 setup.py sdist
    twine upload dist/*

For Open Source Contributors

• Open a Pull request
• State the new feature you are proposing to add or issue you are solving clearly
• Wait for us to approve it. 😉

Notebooks

You can find the notebook here

Project Maintainers

Akshat Anand

Tarushi Pathak

Contributors

Stuti Sehgal

Soumya Snigdha Kundu

License

Made with ❤️ by DS Community SRM