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DFQUICK

A library to create quick custom dataframe. You can create integer columns, category columns and Data Columns easilys

Developed by Marcel Tino (c) 2024

Examples of How To Use the library

You can use this to alter according to your requirements

##syntax
int_column(column name,starting value, ending value, count of rows)
cat_column(column name, Values in a list, count of rows, Probablities of each occurence (Optional))
random_dates(column name,starting date, ending date, count of rows

import pandas as pd
from dfquick import int_column
from dfquick import cat_column
from dfquick import random_dates 

data=int_column("column1", 1, 500, 500)
data=cat_column("Column2",['A','B','C','D'],500,['0.25','0.5','0.1','0.15'])
data=random_dates("Dates",'2020-05-10','2022-05-10',500)

Note: We can create the dataframe using the name data only. You can alter the name later

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Release files for dfquick 0.1.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for dfquick 0.1.4
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Built distribution (wheel)

Table of built distributions (wheels) for dfquick 0.1.4
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dfquick-0.1.4-py3-none-any.whl Python 3 none any Details

Total release size: 5.8 kB

Release files / dfquick-0.1.4.tar.gz

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0.1.4 This release

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