Extracting unique list of strings from Python Dataframe column

Question

I have an example dataframe as given below:

df = 
index                Value     Name         
2019-01-01 07:53:53  10   S_1.M_01
2019-01-01 08:33:52  20   S_1.M_02
2019-01-01 09:13:52  30   S_1.M_03
2019-01-01 09:53:52  40   S_1.M_01
2019-01-01 10:33:52  50   S_1.M_02
2019-01-01 11:13:53  60   S_1.M_03                                                                     
...  ...       ...
2019-09-08 15:38:52  100  8157_S2

Now I want to extract to those columns with name Name and create outputs. How to extract those rows with same names?

My code:

df_grp = iv_df['element'].unique

This did not yield any result.

I want to achieve something like this below different outputs

Output1:

index                Value     Name         
2019-01-01 07:53:53  10   S_1.M_01
2019-01-01 09:53:52  40   S_1.M_01

Output2:

index                Value     Name         
2019-01-01 08:33:52  20   S_1.M_02
2019-01-01 10:33:52  50   S_1.M_02

Output3:

index                Value     Name         
2019-01-01 09:13:52  30   S_1.M_03
2019-01-01 11:13:53  60   S_1.M_03

How to achieve this?

db702 · Accepted Answer · 2019-09-12 01:20:47Z

1

I think there may be code missing from your question, or it isn't clear or I am not fully understanding it. But you can try something like this, where you are iterating through the unique values and creating new dfs.

dfs = []
for val in df.Name.unique():
    dfs.append(df.loc[df.Name == val, :])

This will give you a list, dfs, populated with smaller dfs that are just excerpts of your larger df.

answered Sep 12, 2019 at 1:20

db702

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8 Comments

Mainland Over a year ago

This could create a 26 dataframes. Is there way to extract different outputs? SO I dont have to create 26 dfs

db702 Over a year ago

Instead of appending them to a list, you could just create a temporary df and run whatever operation you need to on the subset.

db702 Over a year ago

Not sure I understand what you mean by 'extract different outputs'

Mainland Over a year ago

What you suggested in your previous comment is what I wanted. Thanks a ton.

db702 Over a year ago

Yes, you could iterate through them again or just before you append to the list and do something like df['new_column'] = None. But it would be better to do that on the original data frame, so that you are only creating a new column once, not 26 times

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