CODEWITHSUNDEEP
python-3.xpandas
agf1997
agf1997

Reputation: 2898

Placing n rows of pandas a dataframe into their own dataframe

I have a large dataframe with many rows and columuns.

An example of the structure is:

a = np.random.rand(6,3)
df = pd.DataFrame(a)

I'd like to split the DataFrame into seperate data frames each consisting of 3 rows.

Upvotes: 1

Views: 34

Answers (2)

piRSquared
piRSquared

Reputation: 294488

you can use groupby

g = df.groupby(np.arange(len(df)) // 3)

for n, grp in g:
    print(grp)

          0         1         2
0  0.278735  0.609862  0.085823
1  0.836997  0.739635  0.866059
2  0.691271  0.377185  0.225146
          0         1         2
3  0.435280  0.700900  0.700946
4  0.796487  0.018688  0.700566
5  0.900749  0.764869  0.253200

to get it into a handy dictionary

mydict = {k: v for k, v in g}

Upvotes: 2

MaxU - stand with Ukraine
MaxU - stand with Ukraine

Reputation: 210882

You can use numpy.split() method:

In [8]: df = pd.DataFrame(np.random.rand(9, 3))

In [9]: df
Out[9]:
          0         1         2
0  0.899366  0.991035  0.775607
1  0.487495  0.250279  0.975094
2  0.819031  0.568612  0.903836
3  0.178399  0.555627  0.776856
4  0.498039  0.733224  0.151091
5  0.997894  0.018736  0.999259
6  0.345804  0.780016  0.363990
7  0.794417  0.518919  0.410270
8  0.649792  0.560184  0.054238

In [10]: for x in np.split(df, len(df)//3):
    ...:     print(x)
    ...:
          0         1         2
0  0.899366  0.991035  0.775607
1  0.487495  0.250279  0.975094
2  0.819031  0.568612  0.903836
          0         1         2
3  0.178399  0.555627  0.776856
4  0.498039  0.733224  0.151091
5  0.997894  0.018736  0.999259
          0         1         2
6  0.345804  0.780016  0.363990
7  0.794417  0.518919  0.410270
8  0.649792  0.560184  0.054238

Upvotes: 2

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