我的groupby的索引列中有负值。我需要将这些数字排序为数字，而不是文本。这是我的小组和我的排序尝试，这是不成功的：
df_counts = df.groupby('DAYSLATE')[['DAYSLATE']].count()
df_counts = df_counts.sort_index().astype(int)
这是我目前的输出：
DAYSLATE DAYSLATE_PCT CUMULATIVE CUM_PCT
DAYSLATE
-1 59 7.73% 59 7.73%
-129 1 0.13% 60 7.86%
-2 7 0.92% 67 8.78%
-230 1 0.13% 68 8.91%
-3 1 0.13% 69 9.04%
0 486 63.7% 555 72.74%
1 98 12.84% 653 85.58%
10 3 0.39% 656 85.98%
11 3 0.39% 659 86.37%
14 2 0.26% 661 86.63%
2 33 4.33% 694 90.96%
260 1 0.13% 695 91.09%
3 18 2.36% 713 93.45%
4 25 3.28% 738 96.72%
5 10 1.31% 748 98.03%
6 3 0.39% 751 98.43%
7 2 0.26% 753 98.69%
70 1 0.13% 754 98.82%
8 4 0.52% 758 99.34%
9 5 0.66% 763 100.0%
答案 0 :(得分：1)
如果你想保留索引，但只想将它排序为数字......
df_counts.iloc[df_counts.index.astype(int).argsort()]
DAYSLATE.1 DAYSLATE_PCT CUMULATIVE CUM_PCT
DAYSLATE
-230 1 0.13% 68 8.91%
-129 1 0.13% 60 7.86%
-3 1 0.13% 69 9.04%
-2 7 0.92% 67 8.78%
-1 59 7.73% 59 7.73%
0 486 63.7% 555 72.74%
1 98 12.84% 653 85.58%
2 33 4.33% 694 90.96%
3 18 2.36% 713 93.45%
4 25 3.28% 738 96.72%
5 10 1.31% 748 98.03%
6 3 0.39% 751 98.43%
7 2 0.26% 753 98.69%
8 4 0.52% 758 99.34%
9 5 0.66% 763 100.0%
10 3 0.39% 656 85.98%
11 3 0.39% 659 86.37%
14 2 0.26% 661 86.63%
70 1 0.13% 754 98.82%
260 1 0.13% 695 91.09%
否则，您可以将索引设置为数字
df_counts.set_index(df_counts.index.astype(int)).sort_index()
DAYSLATE.1 DAYSLATE_PCT CUMULATIVE CUM_PCT
DAYSLATE
-230 1 0.13% 68 8.91%
-129 1 0.13% 60 7.86%
-3 1 0.13% 69 9.04%
-2 7 0.92% 67 8.78%
-1 59 7.73% 59 7.73%
0 486 63.7% 555 72.74%
1 98 12.84% 653 85.58%
2 33 4.33% 694 90.96%
3 18 2.36% 713 93.45%
4 25 3.28% 738 96.72%
5 10 1.31% 748 98.03%
6 3 0.39% 751 98.43%
7 2 0.26% 753 98.69%
8 4 0.52% 758 99.34%
9 5 0.66% 763 100.0%
10 3 0.39% 656 85.98%
11 3 0.39% 659 86.37%
14 2 0.26% 661 86.63%
70 1 0.13% 754 98.82%
260 1 0.13% 695 91.09%