python - 向 pandas 数据框添加一列会用 NA 填充它

Question

我有这个 pandas 数据框:

          SourceDomain                           1  2         3
0  www.theguardian.com     profile.theguardian.com  1  Directed
1  www.theguardian.com  membership.theguardian.com  2  Directed
2  www.theguardian.com   subscribe.theguardian.com  3  Directed
3  www.theguardian.com            www.google.co.uk  4  Directed
4  www.theguardian.com        jobs.theguardian.com  5  Directed

我想添加一个新列，它是像这样创建的 pandas 系列:

Weights = Weights.value_counts()

但是，当我尝试使用 edgesFile[4] = Weights 添加新列时，它会用 NA 而不是值填充它:

          SourceDomain                           1  2         3   4
0  www.theguardian.com     profile.theguardian.com  1  Directed NaN
1  www.theguardian.com  membership.theguardian.com  2  Directed NaN
2  www.theguardian.com   subscribe.theguardian.com  3  Directed NaN
3  www.theguardian.com            www.google.co.uk  4  Directed NaN
4  www.theguardian.com        jobs.theguardian.com  5  Directed NaN

如何添加保留值的新列？谢谢？

丹尼

Answer 1

您得到 NaN 是因为 Weights 的索引与 edgesFile 的索引不匹配。如果您希望 Pandas 忽略 Weights.index 并仅按顺序粘贴值，然后传递底层 NumPy 数组:

edgesFile[4] = Weights.values

<小时/>

下面是一个演示差异的示例:

In [14]: df = pd.DataFrame(np.arange(4)*10, index=list('ABCD'))

In [15]: df
Out[15]: 
    0
A   0
B  10
C  20
D  30

In [16]: s = pd.Series(np.arange(4), index=list('CDEF'))

In [17]: s
Out[17]: 
C    0
D    1
E    2
F    3
dtype: int64

在这里我们看到 Pandas 对齐索引:

In [18]: df[4] = s

In [19]: df
Out[19]: 
    0   4
A   0 NaN
B  10 NaN
C  20   0
D  30   1

在这里，Pandas 只是将 s 中的值粘贴到列中:

In [20]: df[4] = s.values

In [21]: df
Out[21]: 
    0  4
A   0  0
B  10  1
C  20  2
D  30  3