给定.csv文件温度csv在L1x,,,,,,,
0,1,0,0,0,1,1,
0,0,1,0,0,1,0,
0,0,0,1,0,0,1,
0,0,0,0,1,0,0,
1,1,1,1,1,1,1,
1,1,1,1,1,1,1,
1,1,1,1,1,1,1,
1,1,1,1,1,1,1,
读入如下:
^{pr2}$
输出:c0 c1 c2 c3 c4 c5 c6 c7
0 0 1 0 0 0 1 1 NaN
1 0 0 1 0 0 1 0 NaN
2 0 0 0 1 0 0 1 NaN
3 0 0 0 0 1 0 0 NaN
4 1 1 1 1 1 1 1 NaN
5 1 1 1 1 1 1 1 NaN
6 1 1 1 1 1 1 1 NaN
7 1 1 1 1 1 1 1 NaN
最后一列中的“NaN”来自后面讨厌的逗号。范围中的8需要与列数匹配。要访问a中的列,请使用a.c3
或者a[c3]
这两者都会导致0 0
1 0
2 1
3 0
4 1
5 1
6 1
7 1
Name: c3
pandas最酷的一点是,如果你想用XOR两个列,你可以非常简单地。在a.c0^a.c2
输出0 0
1 1
2 0
3 0
4 0
5 0
6 0
7 0
Name: c0