0

I have pandas data frame and want to create 4 other data frames from it, based on distinct values in one column (Let say column A in df). The shape of the data frame called df is (77572, 36). I have a total of 1714 distinct values in column A. The end result should give a total of 4 data frames, with shapes (500, 36).

If we use df['A'].unique() or df.groupby['A'] we get the desirable result structure, but the type of the result is pandas.core.groupby.generic.DataFrameGroupBy for groupby() method, thus make it imposible to furter slice the df like for example:

df1 = df.iloc[:500,:]
df2 = df.iloc[501:1000,:]
df3 = df.iloc[1001:1500,:]
df4 = df.iloc[1501:,:]

How to generate new pandas DataFrame object with shape (1714, 36) - 1714 being distinct values in column A, and make 4 additional data frames from it?

Improve this question
4
  • Can you please explain the logic by which you want to split the dataframe? Do you wish to create a DataFrame for Each unique value of column 'A'? Commented Aug 30, 2021 at 11:04
  • @OfekGlick thanks for your comment. I have a data frame called df. It has a total of 77572 values (rows). It has a total of 1714 distinct values in column A. After I group by column A I get the result as one desirable data frame which I want to further split into 4 data frames using df.iloc[] like explained above. The issue is that when I use group by, I get the desired result but with the type pandas.core.groupby.generic.DataFrameGroupBy which is not a data frame. Commented Aug 30, 2021 at 12:48
  • I'm not sure groupby is what you're looking for, as it is expected to be followed by some aggregation function, you can read more about it here. If you're looking to just create a DataFrame for each unique element in your dataframe I have posted a possible solution. Commented Aug 30, 2021 at 13:31
  • Yes, it might be the case @OfekGlick. The final goal is to create 4 additional data frames, using the original data frame df, but for DISTINCT values in column A. That is why my approach was to first get DISTINCT values using df.groupby('A') and then from the result, create the desired 4 new data frames. Commented Aug 30, 2021 at 14:20
Related questions
1512
Sort (order) data frame rows by multiple columns
822
How do I count the NaN values in a column in pandas DataFrame?
860
How to convert index of a pandas dataframe into a column
Load 6 more related questions Show fewer related questions

0

Reset to default

Start asking to get answers

Find the answer to your question by asking.

Ask question

Explore related questions

See similar questions with these tags.