A python package to help Data Scientists, Machine Learning Engineers and Analysts
Project description
datastand
Why datastand? Data + Understand
A python package to help Data Scientists, Machine Learning Engineers and Analysts better understand data. Gives quick insights about a given dataset.
Installation
Run the following command on the terminal to install the package:
pip install datastand
Usage :
Code:
from datastand import datastand
import pandas as pd
df = pd.read_csv("path/to/target/dataframe")
datastand(df)
Output:
General stats:
==================
Shape of DataFrame: (1202, 13)
Number of unique data types : {dtype('int64'), dtype('O')}
Number of numerical columns: 2
Number of non-numerical columns: 11
Missing data:
=======================
DataFrame contains 2670 missing values (17.09%) as follows column-wise:
-----------------------------------------------------------------------
Gender 41
Car_Category 372
Subject_Car_Colour 697
Subject_Car_Make 248
LGA_Name 656
State 656
dtype: int64
-----------------------------------------------------------------------
Do you wish to long-list missing data statistics?(y/n): y
.
.
.
Code:
# This function is already available in the DataStand class and also available separately
# Here we're running it separately
from datastand import plot_missing
plot_missing(df)
Output:
Code:
from datastand import impute_missing
impute_missing(df)
Output:
Imputing missing data...
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 80/80 [00:02<00:00, 30.52it/s]
Imputation complete.
Author/Maintainer
Vincent N. [LinkedIn] [Twitter]
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
datastand-2.4.4.tar.gz
(540.3 kB
view hashes)
Built Distribution
Close
Hashes for datastand-2.4.4-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b7ec380281b2c6fc04edd146d2ecca6e3bc9b6b8a51dba535d67183c1cc2e99c |
|
MD5 | 914da6bfdbdc242448cb9cc2e9478cd8 |
|
BLAKE2b-256 | 99a7d746559c1a8cb63d6f89ef11124d8ae142b48ba033def06edb27fa672022 |