将Pandas数据帧转换为数据范围

Question

我想转置下表：

Name | State | Value ~~~~~~~~~~~~~~~~~~~~ nameA | state1 | 1 nameA | state2 | 5 nameA | state1 | 9 nameA | state1 | 2 nameB | state2 | 3 nameB | state1 | 1

进入这样一个表：

Name | range1_state1 |range1_state2 | range2_state1 | range2_state2 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ nameA | 2 | 1 | 0 | 1 nameB | 1 | 0 | 1 | 0

如果range1 = [0,5]并且range2 =（5,10）
第二个表中的数据是出现次数 第一张桌子。

谢谢

Answer 1

我认为您需要cut才能使用crosstab：

print (pd.cut(df['Value'], bins=[0, 5, 10], include_lowest=True))
0     [0, 5]
1     [0, 5]
2    (5, 10]
3     [0, 5]
4     [0, 5]
5     [0, 5]
Name: Value, dtype: category
Categories (2, object): [[0, 5] < (5, 10]]

df['rng'] = pd.cut(df['Value'], bins=[0, 5, 10], 
                   labels=['range1','range2'], include_lowest=True)
df['State'] = df['rng'].astype(str) + '_' + df['State']
print (df)
    Name          State  Value     rng
0  nameA  range1_state1      1  range1
1  nameA  range1_state2      5  range1
2  nameA  range2_state1      9  range2
3  nameA  range1_state1      2  range1
4  nameB  range1_state2      3  range1
5  nameB  range1_state1      1  range1

df = pd.crosstab(df.Name, df.State)
print (df)
State  range1_state1  range1_state2  range2_state1
Name                                              
nameA              2              1              1
nameB              1              1              0

编辑：

您可以检查此示例中的分箱值：

df1 = pd.DataFrame({'Value':np.arange(11)})
df1['bins'] = pd.cut(df1['Value'], bins=[0, 5, 10], include_lowest=True)
print (df1)
    Value     bins
0       0   [0, 5]
1       1   [0, 5]
2       2   [0, 5]
3       3   [0, 5]
4       4   [0, 5]
5       5   [0, 5]
6       6  (5, 10]
7       7  (5, 10]
8       8  (5, 10]
9       9  (5, 10]
10     10  (5, 10]