How Pandas extracts text from cells and slices it up

Pandas extracts text from cells and slices it up

For example, there is the following Excel data

Now we want to extract the contents of one of the payment time columns and capture only the specific time on the day of shipment.

Use . () to solve this problem.

The code is as follows:

import pandas as pd

file = pd.read_excel(r"C:\Users\15025\Desktop\uncle\")
time = file["Time of payment"].(11, 19)
print(time)
"""
result.
0 23:57:14
1 23:47:16
2 23:47:15
3 23:43:14
4 23:40:30
5 23:28:40
6 23:28:44
7 23:25:42
8 23:23:57
9 23:22:11
10 23:21:47
Name: payment time, dtype: object
"""

As you can see, we have successfully intercepted the time information in it.

The above methods are morepandasThe write-up.

There is also another alternative

The code is as follows:

import pandas as pd

file = pd.read_excel(r"C:\Users\15025\Desktop\uncle\")

for i in range(len(file["Time of payment"])):
    print(file["Time of payment"][i][11:19])
"""
result:
23:57:14
23:47:16
23:47:15
23:43:14
23:40:30
23:28:40
23:28:44
23:25:42
23:23:57
23:22:11
23:21:47
"""

As you can see, we also managed to get the information we wanted, but we used a loop.

While the speed doesn't feel too slow, a lot of data testing is still needed to show the advantages and disadvantages of both methods.

The first one is currently recommendedpandasThe built-in methods of the

What if you want to work on the last row of data?

The following code can be used:

import pandas as pd

file = pd.read_excel(r"C:\Users\15025\Desktop\uncle\")
time = [-1].tolist()
time1 = [-1]
print(time)
print(time1)
"""
['SXDD202112212321341427301514', '2021-12-21 23:21:34', '2021-12-21 23:21:47', '2021122122001498451403927933', 'G202112212321334217301915']
['SXDD202112212321341427301514' '2021-12-21 23:21:34'
 '2021-12-21 23:21:47' '2021122122001498451403927933'
 'G202112212321334217301915']
"""

You can see that we have successfully converted the last row of data into a list object

Next, you can use list slicing as normal to get the data we need.

summarize

The above is a personal experience, I hope it can give you a reference, and I hope you can support me more.