Python 基于多个条件将列的值填充到数据帧的新列_Python_Pandas_Lambda

Python 基于多个条件将列的值填充到数据帧的新列

python pandas lambda

Python 基于多个条件将列的值填充到数据帧的新列,python,pandas,lambda,Python,Pandas,Lambda,假设我有一个如下的数据框 df.head() col1 col2 col3 start end gs chr1 HAS GEN 11869 14409 DDX chr1 HAS TRANS 11869 14409 NaN chr1 HAS EX 11869 12227 NaN chr1 HAS GEN 12613 12721 FXBZ chr1

假设我有一个如下的数据框

df.head()
col1    col2    col3    start   end     gs
chr1    HAS     GEN     11869   14409   DDX
chr1    HAS     TRANS   11869   14409   NaN
chr1    HAS     EX      11869   12227   NaN
chr1    HAS     GEN     12613   12721   FXBZ
chr1    HAS     EX      13221   14409   NaN
chr1    HAS     EX      12010   12057   NaN

现在，我需要根据两个条件添加一个新列，并且必须从一个列中使用值

例如，条件是

如果
```
col3
```
等于
```
GEN
```
或
```
EX
```
。然后添加一个新列
```
col7
```
，该列的值来自列
```
gs
```
当
```
col3
```
等于
```
GEN
```
时，
```
gs
```
中的值必须始终为该值。这绝不是
```
NaNs
```

最后，我希望我的数据框架如下所示：

col1    col2  col3   start   end     gs     col7
chr1    HAS   GEN    11869   14409   DDX    DDX
chr1    HAS   EX     11869   12227   NaN    DDX
chr1    HAS   TRANS  11869   14409   no
chr1    HAS   GEN    12613   12721   FXBZ   FXBZ
chr1    HAS   EX     13221   14409   NaN    FXBZ
chr1    HAS   EX     12010   12057   NaN    FXBZ

我尝试使用

lambda

：

df.apply(
    lambda row: row['gs'] if (row['col3'] =="EX" and row['gs'] !=NaN) else "no",
    axis=1)

但是，我无法将

gs

列中的值填充到新列中。它设置

NaN

值。这是我不想要的

任何建议都将不胜感激

我相信您可以使用with condition by并向前填充列

gs

中缺少的值：

df['col7'] = np.where(df['col3'].isin(['GEN','EX']), df['gs'].ffill(), 'no')
print (df)
   col1 col2   col3  start    end    gs  col7
0  chr1  HAS    GEN  11869  14409   DDX   DDX
1  chr1  HAS     EX  11869  14409   NaN   DDX
2  chr1  HAS  TRANS  11869  12227   NaN    no
3  chr1  HAS    GEN  12613  12721  FXBZ  FXBZ
4  chr1  HAS     EX  13221  14409   NaN  FXBZ
5  chr1  HAS     EX  12010  12057   NaN  FXBZ

详细信息：

print (df['gs'].ffill())
0     DDX
1     DDX
2     DDX
3    FXBZ
4    FXBZ
5    FXBZ
Name: gs, dtype: object