用Datafram的第一个非零值替换fillna值

Question

我有如下数据帧：

,VM,Storage Capacity MB,Memory Capacity MB,Powerstate,CPUs
0,abc1234,102400.0,4096,poweredOn,1

1,xyz1234,81920.0,4096,poweredOn,1

2,abc1234,,4096,poweredOff,1

3,xyz1234,,4096,poweredOff,1

具有NaN值的行需要替换为非零的第一个匹配。输出需要如下：

,VM,Storage Capacity MB,Memory Capacity MB,Powerstate,CPUs
0,abc1234,102400.0,4096,poweredOn,1

1,xyz1234,81920.0,4096,poweredOn,1

2,abc1234,102400.0,4096,poweredOff,1

3,xyz1234,81920.0,4096,poweredOff,1

使用fillna.method('lasfil')并不能真正替换为第一个匹配

    import pandas 
    file2 = pd.read_csv(r'c:\temp\pd_powerstate_new_south.csv')
    file2 = pd.read_csv(r'c:\temp\pd_powerstate_new_south.csv')
    file1.set_index('VM')
    file2.set_index('VM')
    merged_data = pd.merge(left = file1, right = file2, how = 'outer')
    merged_data.fillna("some custom 
    method").to_csv(r'c:\temp\mergeddata.csv')

实际结果如下：

 ,VM,Storage Capacity MB,Memory Capacity MB,Powerstate,CPUs 0,abc1234,102400.0,4096,poweredOn,1
 1,xyz1234,81920.0,4096,poweredOn,1
 2,abc1234,102400.0,4096,poweredOff,1
 3,xyz1234,81920.0,4096,poweredOff,1

Answer 1

不确定您的数据帧有多少个非NA值。如果只有几个，可以尝试df.ffill（）.bfill（）或df.bfill（）.ffill（）的组合，只取找到的非na值并向前/向后扩展

如果有许多非na值，我建议通过在列中循环来解决：

for col in merged_data.columns:
    first_non_na_value = merged_data[col].dropna().iloc[0]
    merged_data[col] = merged_data[col].fillna(first_non_na_value)