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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

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Expected Output: Based on Three different Dates

First DataFrame: df_23

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Second DataFrame: df_24

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Third DataFrame: df_25

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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.

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

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Analyst
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  • Possible duplicate of [Python - splitting dataframe into multiple dataframes based on column values and naming them with those values](https://stackoverflow.com/questions/40498463/python-splitting-dataframe-into-multiple-dataframes-based-on-column-values-and) – Umar.H Oct 16 '19 at 22:08
  • @Datanovice: I tried using the similar code but I am not getting the expected output! – Analyst Oct 17 '19 at 14:39
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    [You should not post code as an image because...](https://meta.stackoverflow.com/a/285557/1422451) – Parfait Oct 17 '19 at 14:49
  • @Parfait: Sure! I don't know about that. Thanks for suggestion. – Analyst Oct 17 '19 at 16:04

1 Answers1

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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
Umar.H
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  • 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 – Analyst Oct 17 '19 at 16:14
  • @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. – Umar.H Oct 17 '19 at 16:24
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    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. – Analyst Oct 17 '19 at 16:49