I have a dataframe like below and I want to add another column that is replicated untill certain condition is met.
sample_df = pd.DataFrame(data={
'id': ['A', 'B', 'C'],
'n' : [ 1, 2, 3],
'v' : [ 10, 13, 8],
'z' : [5, 3, 6],
'g' : [8, 8, 10]
})
additional_rows=
Now I want to add another column which contains additional information about the dataframe. For instance, I want to replicate Yes untill id is B and No when it is below B and Yes from C to D and from from D to E Maybe.
The output I am expecting is as follows:
sample_df = pd.DataFrame(data={
'id': ['A', 'B', 'C','G','D','E'],
'n' : [ 1, 2, 3, 5, 5, 9],
'v' : [ 10, 13, 8, 8, 4 , 3],
'z' : [5, 3, 6, 9, 9, 8],
'New Info': ['Yes','Yes','No','No','Maybe','Maybe']
})
sample_df
id n v z New Info
0 A 1 10 5 Yes
1 B 2 13 3 Yes
2 C 3 8 6 No
3 G 5 8 9 No
4 D 5 4 9 Maybe
5 E 9 3 8 Maybe
How can I achieve this in python?
You can use np.select to return results based on conditions. Since you were talking more about positional conditions I used df.index:
sample_df = pd.DataFrame(data={
'id': ['A', 'B', 'C','G','D','E'],
'n' : [ 1, 2, 3, 5, 5, 9],
'v' : [ 10, 13, 8, 8, 4 , 3],
'z' : [5, 3, 6, 9, 9, 8]
})
sample_df['New Info'] = np.select([sample_df.index<2, sample_df.index<4],['Yes', 'No'], 'Maybe')
sample_df
Out[1]:
id n v z New Info
0 A 1 10 5 Yes
1 B 2 13 3 Yes
2 C 3 8 6 No
3 G 5 8 9 No
4 D 5 4 9 Maybe
5 E 9 3 8 Maybe
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