python - Pandas:如何提取匹配 Filter1 或 filter2 的数据帧的行

Question

例如，我有一个看起来像这样的 pandas 数据框:

label          Y88_N          diff       div      fold  
0       25273.626713  17348.581851  2.016404  2.016404  
1       29139.510491  -4208.868050  0.604304 -0.604304  
2       34388.439717 -30147.834699  0.458903 -0.458903  
3       69704.254089 -32976.152490  0.116894 -0.116894  
4      193717.440783 -71359.494098  0.286045 -0.286045  
5       28996.634708  10934.944533  2.031293  2.031293  
6       45021.782930    680.437629  1.056383  1.056383  

但有数千行。当“折叠”列中的值时，我想获得一个包含行的新数据框> 2 或 < 0.6。所以最后数据框应该是这样的:

label          Y88_N          diff       div      fold  
0       25273.626713  17348.581851  2.016404  2.016404  
1       29139.510491  -4208.868050  0.604304 -0.604304  
5       28996.634708  10934.944533  2.031293  2.031293

我尝试过不同的方法，例如:

def ranged(start, end, step):
x = start
    while x < end:
        yield x
        x += step
df2 = df[~df['fold'].isin(ranged(-0.6, 2, 0.000001))]

或

df2 = df[(df['fold'] >= 2) & (df['fold'] <= -0.6)]

但似乎没有任何效果有没有一种简单的方法可以选择与过滤器 1 或过滤器 2 匹配的列中的值？谢谢

Answer 1

你可以做

In [276]: df[(df['fold'] >= 2) | (df['fold'] <= -0.6)]
Out[276]:
   label         Y88_N          diff       div      fold
0      0  25273.626713  17348.581851  2.016404  2.016404
1      1  29139.510491  -4208.868050  0.604304 -0.604304
5      5  28996.634708  10934.944533  2.031293  2.031293

或者使用类似query的方法

In [277]: df.query('fold >=2 | fold <=-0.6')
Out[277]:
   label         Y88_N          diff       div      fold
0      0  25273.626713  17348.581851  2.016404  2.016404
1      1  29139.510491  -4208.868050  0.604304 -0.604304
5      5  28996.634708  10934.944533  2.031293  2.031293

而且，pd.eval() 适用于包含大型数组的表达式

In [278]: df[pd.eval('df.fold >=2 | df.fold <=-0.6')]
Out[278]:
   label         Y88_N          diff       div      fold
0      0  25273.626713  17348.581851  2.016404  2.016404
1      1  29139.510491  -4208.868050  0.604304 -0.604304
5      5  28996.634708  10934.944533  2.031293  2.031293