CODEWITHSUNDEEP
pythonpandasloops
Porsche Adams
Porsche Adams

Reputation: 5

Create multiple data frames from one -python

I have a large file (>500 rows) with multiple data points for each unique item in the list, something like :

cheese weight location
gouda 1.4 AL
gouda 2 TX
gouda 1.2 CA
cheddar 5.3 AL
cheddar 6 MN
chaddar 2 WA
Havarti 4 CA
Havarti 4.2 AL

I want to make data frames for each cheese to store the relevant data

I have this:

main_cheese_file = pd.read_csv('CheeseMaster.csv')

cut_the_cheese = main_cheese_file.cheese.unique()
melted = {elem: pd.DataFrame() for elem in cut_the_cheese}

for slice in melted.slice():
    melted[slice] = main_cheese_file[:][main_cheese_file.cheese == slice]

to split it up on the unique thing I want.

What I want to do with it is make df's that can be exported for each cheese with the cheese name as the file name.

So far I can force it with

 melted['Cheddar'].to_csv('Cheddar.csv')

and get the Cheddars ....

but I don't want to have to know and type out each type of cheese on the list of 500 rows...

Is there a way to add this to my loop?

Upvotes: 0

Views: 30

Answers (1)

It_is_Chris
It_is_Chris

Reputation: 14063

You can just iterate over a groupby object

import pandas as pd

df = pd.read_csv('CheeseMaster.csv')
for k,v in df.groupby('cheese'):
    v.to_csv(f'{k}.csv', index=False)

Upvotes: 1

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