Question

CSV文件：（sample1.csv）

Location_City, Location_State, Name, hobbies
Los Angeles,   CA,             John, "['Music', 'Running']"
Texas,         TX,             Jack, "['Swimming', 'Trekking']"

我想将CSV的兴趣爱好列转换为以下输出

Location_City, Location_State, Name, hobbies
Los Angeles,   CA,             John, Music
Los Angeles,   CA,             John, Running
Texas,         TX,             Jack, Swimming
Texas,         TX,             Jack, Trekking

我已将csv读入dataframe，但不知道如何转换？

 data = pd.read_csv("sample1.csv") 
 df=pd.DataFrame(data)
 df

Answer 1

您可以使用findall或extractall从hobbies列中获取列表，然后用chain.from_iterable展平并重复另一列：

a = df['hobbies'].str.findall("'(.*?)'").astype(np.object)
lens = a.str.len()

from itertools import chain

df1 = pd.DataFrame({
    'Location_City' : df['Location_City'].values.repeat(lens),
    'Location_State' : df['Location_State'].values.repeat(lens),
    'Name' : df['Name'].values.repeat(lens),
    'hobbies' : list(chain.from_iterable(a.tolist())), 
})

或创建Series，删除第一级并将join移至原始DataFrame：

df1 = (df.join(df.pop('hobbies').str.extractall("'(.*?)'")[0]
               .reset_index(level=1, drop=True)
               .rename('hobbies'))
         .reset_index(drop=True))

print (df1)

  Location_City Location_State  Name   hobbies
0   Los Angeles             CA  John     Music
1   Los Angeles             CA  John   Running
2         Texas             TX  Jack  Swimming
3         Texas             TX  Jack  Trekking

Answer 2

我们可以使用 pandas.DataFrame.explode 版本中引入的 0.25.0 函数解决这个问题，如果您有相同或更高版本，您可以使用以下代码。
爆炸函数参考：https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.explode.html

import pandas as pd
import ast

data = {
    'Location_City': ['Los Angeles','Texas'],
    'Location_State': ['CA','TX'],
    'Name': ['John','Jack'],
    'hobbies': ["['Music', 'Running']", "['Swimming', 'Trekking']"]
}
df = pd.DataFrame(data)

# Converting a string representation of a list into an actual list object

list_eval = lambda x: ast.literal_eval(x)
df['hobbies'] = df['hobbies'].apply(list_eval)

# Exploding the list
df = df.explode('hobbies')

print(df)

  Location_City Location_State  Name   hobbies
0   Los Angeles             CA  John     Music
0   Los Angeles             CA  John   Running
1         Texas             TX  Jack  Swimming
1         Texas             TX  Jack  Trekking

使用Dataframe将CSV列值转换为多行

2 个答案: