Question

I have a dataframe like this where the columns are the scores of some metrics:

I want to create a new column to summarize which metrics each row scored over a set threshold in, using the column name as a string. So if the threshold was A > 2, B > 3, C > 1, D > 3, I would want the new column to look like this:

A B C D NewCol  
4 3 3 1 AC  
2 5 2 2 BC  
3 5 2 4 ABCD

I tried using a series of np.where:

df[NewCol] = np.where(df['A'] > 2, 'A', '')  
df[NewCol] = np.where(df['B'] > 3, 'B', '')

etc.

but realized the result was overwriting with the last metric any time all four metrics didn't meet the conditions, like so:

A B C D NewCol  
4 3 3 1 C  
2 5 2 2 C  
3 5 2 4 ABCD

I am pretty sure there is an easier and correct way to do this.

Answer 1

您可以这样做：

import pandas as pd

data = [[4, 3, 3, 1],
        [2, 5, 2, 2],
        [3, 5, 2, 4]]

df = pd.DataFrame(data=data, columns=['A', 'B', 'C', 'D'])

th = {'A': 2, 'B': 3, 'C': 1, 'D': 3}

df['result'] = [''.join(k for k in df.columns if record[k] > th[k]) for record in df.to_dict('records')]

print(df)

输出

   A  B  C  D result
0  4  3  3  1     AC
1  2  5  2  2     BC
2  3  5  2  4   ABCD

Answer 2

使用dot

s=pd.Series([2,3,1,3],index=df.columns)
df.gt(s,1).dot(df.columns)
Out[179]: 
0      AC
1      BC
2    ABCD
dtype: object

#df['New']=df.gt(s,1).dot(df.columns)

Answer 3

另一个以数组方式运行的选项。比较性能会很有趣。

import pandas as pd
import numpy as np

# Data to test.

data = pd.DataFrame(
    [
        [4, 3, 3, 1],
        [2, 5, 2, 2],
        [3, 5, 2, 4]
    ]
    , columns = ['A', 'B', 'C', 'D']
)

# Series to hold the thresholds.

thresholds = pd.Series([2, 3, 1, 3], index = ['A', 'B', 'C', 'D'])

# Subtract the series from the data, broadcasting, and then use sum to concatenate the strings.

data['result'] = np.where(data - thresholds > 0, data.columns, '').sum(axis = 1)

print(data)

礼物：

   A  B  C  D result
0  4  3  3  1     AC
1  2  5  2  2     BC
2  3  5  2  4   ABCD

Create a column in a dataframe that is a string of characters summarizing data in other columns

3 个答案: