[Python] Select a range of data based on a selected value using Pandas

I have a dataframe, I need to select a range of data based on a month value, but the result expected is always showing six rows where the month selected appears in the filtered data , here's the code :

import pandas as pd

data = {
"function": ["test1","test2","test3","test4","test5","test6","test7","test8","test9","test10","test11","test12"],
"service": ["A", "B", "AO", "M" ,"A", "PO", "MP", "YU", "Z", "R", "E", "YU"],
"month": ["January","February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December"]
}

df = pd.DataFrame(data)

selected_month = "January"
selected_month_idx = df[df["month"] == selected_month].index[0]
six_months_indices = [i % len(df) for i in range(selected_month_idx - 2, selected_month_idx + 4)]
six_months_df = df.loc[six_months_indices] # add .reset_index(drop=True) if needed
print(six_months_df)


output :

function service month
10 test11 E November
11 test12 YU December
0 test1 A January
1 test2 B February
2 test3 AO March
3 test4 M April


the issue with this code is when I select January for example, the order of the months is not good, what I expet is somthing like that :

function service month
0 test1 A January
1 test2 B February
2 test3 AO March
3 test4 M April
3 test5 A May
3 test6 PO June


when I select December for example the output should be :

function service month
6 test7 MP July
7 test8 YU August
8 test9 Z September
9 test10 R October
10 test11 E November
11 test12 YU December


when I select Octobre the output should be for example :

function service month
6 test7 MP July
7 test8 YU August
8 test9 Z September
9 test10 R October
10 test11 E November
11 test12 YU December


the order of the month displated matters, always min(month) => max(month) output like this is not expected :

output :

function service month
10 test11 E November
11 test12 YU December
0 test1 A January
1 test2 B February
2 test3 AO March
3 test4 M April


anyone please could to adjust the code above,

thanks

Continue reading...