Create different dataframe inside of a 'for' loop

Question

I have a dataset that looks something like the following. I would like to create dataframes that contains only texts for each authors, for example as you can see the df1 contains only texts from the author0, etc. Is there any way to do that for many authors?

import pandas as pd

data = {
    'text' : ['text0', 'text1', 'text2'],
    'author': ['author0', 'author1', 'author1'],
    'title': ['Comunicación', 'Administración', 'Ventas']
}

df = pd.DataFrame(data)
df1 = df[df["author"]=="author0"]

df2 = df[df["author"]=="author1"]

I have tried this, but it’s not working

list_author = df['author'].unique().tolist()
for i in list_author: 
  dt_str(i) = dt[dt["author"]=="i"]

It would be helpful if the data frames have the name df_’author’ (eg df_George)

Asked By: John Angelopoulos

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Source

Answer 1

If you want to have separate dataframes per author, use a dictionary with the author names as the keys. See the below example:

data = {
    'text' : ['text0', 'text1', 'text2'],
    'author': ['author0', 'author1', 'author1'],
    'title': ['Comunicación', 'Administración', 'Ventas']
}

df = pd.DataFrame(data)
df_dict = {}
for author in df['author'].unique():
    df_dict[author] = df[df['author']==author]

print(df_dict.keys())
#dict_keys(['author0', 'author1'])

print(df_dict['author0'])
#     text   author         title
# 0  text0  author0  Comunicación

print(df_dict['author1'])
#     text   author           title
# 1  text1  author1  Administración
# 2  text2  author1          Ventas

Answered By: JarroVGIT

Create different dataframe inside of a 'for' loop

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