两列之间的日期范围

Question

Im kinda new to Python and Datascience.

I have a Dataset with 2 datetime columns A and B :

                     A                    B
0  2019-03-13 08:12:20  2019-03-13 08:12:25
1  2019-03-15 10:02:18  2019-03-13 10:02:20

For each row, i want to generate the date range in seconds between column A and column B, so as a result i should get this:

                    A
0 2019-03-13 08:12:20
1 2019-03-13 08:12:21
2 2019-03-13 08:12:22
3 2019-03-13 08:12:23
4 2019-03-13 08:12:24
5 2019-03-13 08:12:25

I made it work with this:

import pandas as pd, numpy as np

df=pd.DataFrame({'A': ["2019-03-13 08:12:20", "2019-03-15 10:02:18"], 'B': ["2019-03-13 08:12:25", "2019-03-13 10:02:20"]})
l=[pd.date_range(start=df.iloc[i]['A'], end=df.iloc[i]['B'], freq='S') for i in range(len(df))]
df1=(pd.DataFrame(l).T)[0]
print(df1)

But as i have like 1M rows, it's taking too much time to run and i know that this solution isn't really the best, can you please guys show me whats the best way to do this?

Answer 1

Here is necessary loop, one possible solution with list comprehension and flattening:

l = [x for a, b in zip(df.A, df.B) for x in pd.date_range(a, b, freq='S')]
df1= pd.DataFrame({'A':l})
print(df1)
                    A
0 2019-03-13 08:12:20
1 2019-03-13 08:12:21
2 2019-03-13 08:12:22
3 2019-03-13 08:12:23
4 2019-03-13 08:12:24
5 2019-03-13 08:12:25

Another solution:

df1 = (pd.concat([pd.Series(pd.date_range(r.A, r.B, freq='S')) for r in df.itertuples()])
         .to_frame('A'))
print (df1)
                    A
0 2019-03-13 08:12:20
1 2019-03-13 08:12:21
2 2019-03-13 08:12:22
3 2019-03-13 08:12:23
4 2019-03-13 08:12:24
5 2019-03-13 08:12:25