Python: Split DataFrame into Dict of DataFrames, based on range of values

Question

I have a DataFrame df that I need to split based on whether the value in a specific column ColB is within a given range;

1-3, 3-5, 5-7 etc

Input:

Time ColA ColB ColC
1    100  1.1  500
2    105  3.2  600
3    107  7.7  550
4    106  2.4  750
5    104  5.2  950
6    103  6.9  450

Desired Output:

Time ColA ColB ColC
1    100  1.1  500
4    106  2.4  750


Time ColA ColB ColC
2    105  3.2  600



Time ColA ColB ColC
3    107  7.7  550
5    104  5.2  950
6    103  6.9  450

Is there a nice way to do this without creating a loop in Python? Also, would it be more efficient to store the output as a list of DataFrames or a Dictionary of Dataframes? I ask as its a fairly large dataset.

Riley · Accepted Answer · 2021-10-28 12:31:35Z

2

Use pandas.cut

https://pandas.pydata.org/docs/reference/api/pandas.cut.html

ie.

groups = pd.cut(df["ColB"], [1,3,5,7])
[d for _, d in df.groupby(groups)]

answered Oct 28, 2021 at 12:31

Riley

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1 Comment

Iceberg_Slim Over a year ago

Thanks, this is a nice solution. I get a buffer size error when changing out the cut values with pre defined array, but I'll try to figure that one out. Apologies for the simple question!

gbruenjes · Accepted Answer · 2021-10-28 12:30:39Z

2

You can try this:

lst = [(1,3), (3,5), (5,7)]
result = [df[df['ColB'].between(a,b)] for a,b in lst]
for i in result:
    print(i, "\n")
    
   Time  ColA  ColB  ColC
0     1   100   1.1   500
3     4   106   2.4   750 

   Time  ColA  ColB  ColC
1     2   105   3.2   600 

   Time  ColA  ColB  ColC
4     5   104   5.2   950
5     6   103   6.9   450

answered Oct 28, 2021 at 12:30

gbruenjes

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