Creating Multiple DataFrames from single DataFrame based on different values of single column

Question

I have 3 days of time series data with multiple columns in it. I have one single DataFrame which includes all 3 days data. I want 3 different DataFrames based on Column name "Dates" i.e df["Dates"]

For Example:

Available Dataframe is: df

Expected Output: Based on Three different Dates

First DataFrame: df_23

Second DataFrame: df_24

Third DataFrame: df_25

I want to use these all three DataFrames separately for analysis.

I tried below code but I am not able to use those three dataframes (Rather I don't know how to use.) Can anybody help me to work my code better. Thank you.

Above code is just printing the DataFrame in three DataFrames that too not as expected as per code!

Possible duplicate of Python - splitting dataframe into multiple dataframes based on column values and naming them with those values — Umar.H
– Umar.H, Commented Oct 16, 2019 at 22:08
@Datanovice: I tried using the similar code but I am not getting the expected output! — Analyst
– Analyst, Commented Oct 17, 2019 at 14:39
@Parfait: Sure! I don't know about that. Thanks for suggestion. — Analyst
– Analyst, Commented Oct 17, 2019 at 16:04

Umar.H · Accepted Answer · 2019-10-17 16:23:51Z

1

Unsure if your saving your variable into a csv or keep it in memory for further use,

you could pass each unique value into a dict and access by it's value :

    print(df)
     Cal  Dates
0    85     23
1    75     23
2    74     23
3    97     23
4    54     24
5    10     24
6    77     24
7    95     24
8    58     25
9    53     25
10   44     25
11   94     25



d = {}

for frame, data in df.groupby('Dates'):
    d[f'df{frame}'] = data


print(d['df23'])
    Cal  Dates
0   85     23
1   75     23
2   74     23
3   97     23

edit updated request :

for k,v in d.items():
    i = (v['Cal'].loc[v['Cal'] > 70].count())
    print(f"{v['Dates'].unique()[0]} --> {i} times")
23 --> 4 times
24 --> 2 times
25 --> 1 times

edited Oct 17, 2019 at 16:23

answered Oct 17, 2019 at 14:53

Umar.H

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3 Comments

Analyst Over a year ago

If I want to iterate through Index values and dictionary (d--> dictionary of df) How can I do that? For Example: If I want to count how many times 'cal' column values are exceeding '70' per day! Expected output from your dataframe should be: on 23 --> 4 Times, on 24--> 2 times and on25--> 1Time

Umar.H Over a year ago

@Analyst updated for you - but this is basic for looping and working with python data types, I suggest you look at some basic tutorials for python and maybe search SO a little :) ask a new question if things get to complex but always post your data as text, show your code and paste any errors.

Analyst Over a year ago

Yeah Thanks. I will do that from next for sure. I am trying out. I will post my code and error too for reference as well. Thanks for suggestions. Appreciate for that.

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