Question

如何打开此DataFrame的第一列，该列是字符串和整数混合

df = pd.DataFrame(
    [
        ["title1", "a", "b", "c", "d"],
        [1, 2, 3, 4, 5],
        [10, 2, 3, 4, 5],
        [100, 2, 3, 4, 5],
        ["title2", "a", "b", "c", "d"],
        [1, 2, 3, 4, 5],
        [10, 2, 3, 4, 5],
        [100, 2, 3, 4, 5],
        ["title3", "a", "b", "c", "d"],
        [1, 2, 3, 4, 5],
        [10, 2, 3, 4, 5],
        [100, 2, 3, 4, 5],
    ]
)

看起来像这样

title1  a   b   c   d
1       2   3   4   5
10      2   3   4   5
100     2   3   4   5
title2  a   b   c   d
1       2   3   4   5
10      2   3   4   5
100     2   3   4   5
title3  a   b   c   d
1       2   3   4   5
10      2   3   4   5
100     2   3   4   5

放入MultiIndex，其中顶层是字符串，第二层是整数？

            a   b   c   d
title1  1   2   3   4   5
        10  2   3   4   5
        100 2   3   4   5
title2  1   2   3   4   5
        10  2   3   4   5
        100 2   3   4   5
title3  1   2   3   4   5
        10  2   3   4   5
        100 2   3   4   5

Answer 1

使用：

#get mask for distingusih strings values in column 0
m = pd.to_numeric(df[0], errors='coerce').isna()
#alternative
#m = ~df[0].astype(str).str.isnumeric()
#create new column 0 filled with strings
df.insert(0, 'a', df[0].where(m).ffill())
#mask for filter not same values in both columns
m1 = df['a'].ne(df[0])
#create MultiIndex
df = df.set_index(['a', 0])
#assign new columns names by first row
df.columns = df.iloc[0]
#filter out by mask and remove index, columns names
df = df[m1.values].rename_axis((None, None)).rename_axis(None, axis=1)
print (df)
            a  b  c  d
title1 1    2  3  4  5
       10   2  3  4  5
       100  2  3  4  5
title2 1    2  3  4  5
       10   2  3  4  5
       100  2  3  4  5
title3 1    2  3  4  5
       10   2  3  4  5
       100  2  3  4  5

Answer 2

此类问题的关键是创建一个布尔级数，以标识level_0索引的位置

<Picker> 
    { this.state.data.map((item)=> <Item label={item} value={item} />) }
<Picker>

熊猫将列转换为MultiIndex

2 个答案: