simple-dataframe-generator 1.0.3

Generate pandas DataFrame quick and easy.

simple_dataframe_generator

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Personal project to generate pandas DataFrame quick and easy.

Installation

pip install simple-dataframe-generator==1.0.3

Supported column types

1. Integer - add_int_col()
2. Float - add_float_col()
3. Categorical - add_cat_col()
4. Datetime - add_datetime_col()

All column types support allow_none.

Usage

import pandas as pd
import numpy as np
from simple_dataframe_generator import SDG


sdg = SDG()

# add integer column with specified parameters
sdg.add_int_col(col_name='age', min_val=0, max_val=99)

# add integer column with specified parameters, allow missing values
sdg.add_int_col(col_name='favorite_number', min_val=-100, max_val=100, allow_none=True, none_prob=10)

# add float column with specified parameters
sdg.add_float_col('distance', min_val=0.0, max_val=200.0)

# add categorical column with pre-defined categories
categories = ['New York', 'Chicago', 'Los Angeles']
sdg.add_cat_col('city', categories=categories, allow_none=True)

# add datetime column
sdg.add_datetime_col('last_seen', min_date='2020-01-01', max_date='2023-02-01')

# generate pandas DataFrame with specific row count
df = sdg.generate_dataframe(rows=10)

Result

	age	favorite_number	distance	city	last_seen
0	69	81	184.517	Chicago	2022-08-12 10:39:59
1	73	1	118.874	Chicago	2021-01-06 11:57:22
2	10	33	199.226	New York	2020-05-29 10:37:36
3	47	-36	194.205	Chicago	2022-05-30 21:26:24
4	25	-66	24.9345	<NA>	2021-03-26 03:19:09
5	36	-12	21.0734	New York	2021-01-19 03:22:27
6	21	<NA>	165.243	Chicago	2022-01-24 04:20:39
7	37	<NA>	3.48131	Chicago	2020-05-30 18:37:24
8	61	-77	90.0552	New York	2021-01-07 14:43:35
9	21	-19	173.3	Los Angeles	2020-01-01 00:53:00

Author

• jmatusov