[英]How do I manipulate a Dataframe with Pivot_Table in Python
I have spent much time on this but I am nowhere closer to a solution.我在这方面花了很多时间,但我离解决方案还很远。
I have a dataframe which outputs as我有一个 dataframe 输出为
RegionID AreaID Year Jan Feb Mar Apr May Jun
0 20.0 1.0 2020.0 1174.0 1056.0 1051.0 1107.0 1097.0 1118.0
1 19.0 2.0 2020.0 460.0 451.0 421.0 421.0 420.0 457.0
2 20.0 3.0 2020.0 2723.0 2594.0 2590.0 2399.0 2377.0 2331.0
3 21.0 4.0 2020.0 863.0 859.0 813.0 785.0 757.0 765.0
4 19.0 5.0 2020.0 4037.0 3942.0 4069.0 3844.0 3567.0 3721.0
5 19.0 6.0 2020.0 1695.0 1577.0 1531.0 1614.0 1671.0 1693.0
6 18.0 7.0 2020.0 1757.0 1505.0 1445.0 1514.0 1406.0 1444.0
7 18.0 8.0 2020.0 832.0 721.0 747.0 852.0 885.0 872.0
8 18.0 9.0 2020.0 2538.0 2000.0 2026.0 1981.0 1987.0 1949.0
9 21.0 10.0 2020.0 1145.0 1235.0 1114.0 1161.0 1150.0 1189.0
10 20.0 11.0 2020.0 551.0 497.0 503.0 472.0 505.0 532.0
11 19.0 12.0 2020.0 1664.0 1526.0 1389.0 1373.0 1384.0 1404.0
12 21.0 13.0 2020.0 381.0 351.0 299.0 286.0 297.0 319.0
13 21.0 14.0 2020.0 1733.0 1627.0 1567.0 1561.0 1498.0 1511.0
14 18.0 15.0 2020.0 1257.0 1257.0 1160.0 1172.0 1124.0 1113.0
I want to pivot this data so that I have a month combined field like below
RegionID AreaID Year Month Amout
20.0 1.0 2020 Jan 1174
20.0 1.0 2020 Feb 1056
20.0 1.0 2020 Mar 1051
Can this be done using pandas? I have been trying with the pivot_table but I cant get it to work.
I hope I've understood your question well.我希望我已经很好地理解了你的问题。 You can
.set_index()
and then .stack()
:你可以
.set_index()
然后.stack()
:
print(
df.set_index(["RegionID", "AreaID", "Year"])
.stack()
.reset_index()
.rename(columns={"level_3": "Month", 0: "Amount"})
)
Prints:印刷:
RegionID AreaID Year Month Amount
0 20.0 1.0 2020.0 Jan 1174.0
1 20.0 1.0 2020.0 Feb 1056.0
2 20.0 1.0 2020.0 Mar 1051.0
3 20.0 1.0 2020.0 Apr 1107.0
4 20.0 1.0 2020.0 May 1097.0
5 20.0 1.0 2020.0 Jun 1118.0
6 19.0 2.0 2020.0 Jan 460.0
7 19.0 2.0 2020.0 Feb 451.0
8 19.0 2.0 2020.0 Mar 421.0
9 19.0 2.0 2020.0 Apr 421.0
10 19.0 2.0 2020.0 May 420.0
11 19.0 2.0 2020.0 Jun 457.0
...
Or:或者:
print(
df.melt(
["RegionID", "AreaID", "Year"], var_name="Month", value_name="Amount"
)
)
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