arv-easy-analysis 0.1.0

Data Analysis makes easy.

Easy Analysis

Use this package to perform Data Analysis easily.

Installation

pip install arv-easy-analysis

Examples

For examples, we are working on tips dataset from seaborn library.

import seaborn as sns
tips = sns.load_dataset("tips")

1. data.summary module.

Get the custom and more insightful summary of your data.

from easy_analysis.data import summary

summary.custom_describe(tips[["total_bill", "tip", "size"]])

Output:

	total_bill	tip	size
count	244	244	244
mean	19.786	2.998	2.57
std	8.902	1.384	0.951
min	3.07	1	1
1%	7.25	1	1
5%	9.558	1.44	2
25%	13.348	2	2
50%	17.795	2.9	2
75%	24.127	3.562	3
95%	38.061	5.196	4
99%	48.227	7.214	6
max	50.81	10	6
skew	1.133	1.465	1.448
kurtosis	1.218	3.648	1.732
notnull	244	244	244
isnull	0	0	0

2. data.outliers module

This function extract the outliers from the given dataset using IQR method and returns the dataframe.

from easy_analysis.data import outliers
outliers.extract_outliers(tips[["total_bill", "tip", "size"]], "total_bill")

Output:

total_bill	tip	size
50.81	10	3
48.33	9	4
48.27	6.73	4
48.17	5	6
45.35	3.5	3
44.3	2.5	3
43.11	5	4
41.19	5	5
40.55	3	2

3. plots.univariate module

Use it for comprehensive univariate plots.

from easy_analysis.plots import univariate
univariate.visualize_feature(tips["total_bill"])

4. plots.insights

Use insights.null_plot function to get overview of null values in a graph.

from easy_analysis.plots import insights
insights.null_plot(tips)  # Output: A graph which gives a overview of null values.

Issues

If you have any issue or query related to this project you can raise here.

Authors

• @arv-anshul