import pandas
import numpy
names = ['a', 'b', 'c']
df = pandas.DataFrame([1, 2, 3, numpy.nan, numpy.nan, 4, 5, 6, numpy.nan, numpy.nan, 7, 8, 9])
For the above one, how will the condition change? Can someone please explain? how can I get this,
df1 =
0
0 1.0
1 2.0
2 3.0
df2 =
0
4 4.0
5 5.0
6 6.0
df3 =
0
8 7.0
9 8.0
10 9.0
You can generate a temporary column, remove NaNs, and group by the temporary column:
dataframes = {f'df{idx+1}': d for idx, (_, d) in enumerate(df.dropna().groupby(df.assign(cond=df.isna().cumsum()).dropna()['cond']))}
Output:
>>> dataframes
{'df1': 0
0 1.0
1 2.0
2 3.0,
'df2': 0
5 4.0
6 5.0
7 6.0,
'df3': 0
10 7.0
11 8.0
12 9.0}
>>> dataframes['df1']
0
0 1.0
1 2.0
2 3.0
>>> dataframes['df2']
0
5 4.0
6 5.0
7 6.0
>>> dataframes['df3']
0
10 7.0
11 8.0
12 9.0
