如何使用pandas根据列id将多个csv文件合并为一个文件

我有4个CSV文件和数千行，所以我会在这里快速复制这些文件

'zip','econ_risk_score'
'22011','5'

'zip','food_risk_score'
'22011','2'

'zip','healthlit_risk_score'
'22011','4'

'zip','housing_risk_score'
'22011','5'

我的结果表应该是这样的

'zip','econ_risk_score','food_risk_score','healthlit_risk_score','housing_risk_score'
'22011','5','2','4','5'

到目前为止，这是我的代码，但我不断得到错误

merge() missing 1 required positional argument: 'right' and can't seem to fix it.

请让我知道你的想法，谢谢

import pandas as pd

df1= pd.read_csv('econ_risk_zip.csv')
df2= pd.read_csv('food_risk_zip.csv')
df3= pd.read_csv('health_risk_zip.csv')
df4= pd.read_csv('housing_risk_zip.csv')

df = pd.merge([df1,df2,df3,df4], right_on = 'zip')
df.to_csv('risk_combined.csv')

---

可以逐个合并数据帧：

df1= pd.read_csv('econ_risk_zip.csv', quotechar="'")
df2= pd.read_csv('food_risk_zip.csv', quotechar="'")
df3= pd.read_csv('health_risk_zip.csv', quotechar="'")
df4= pd.read_csv('housing_risk_zip.csv', quotechar="'")

df = df1.merge(df2, on="zip").merge(df3, on="zip").merge(df4, on="zip")
df.to_csv('risk_combined.csv')

---

可以逐个合并数据帧：

df1= pd.read_csv('econ_risk_zip.csv', quotechar="'")
df2= pd.read_csv('food_risk_zip.csv', quotechar="'")
df3= pd.read_csv('health_risk_zip.csv', quotechar="'")
df4= pd.read_csv('housing_risk_zip.csv', quotechar="'")

df = df1.merge(df2, on="zip").merge(df3, on="zip").merge(df4, on="zip")
df.to_csv('risk_combined.csv')

---

你可以用reduce减少写作。只需指定一个文件列表，然后就可以合并它们，这样，如果需要添加文件，只需修改文件列表即可

from functools import reduce
import pandas as pd

files = ['econ_risk_zip.csv', 'food_risk_zip.csv',
         'health_risk_zip.csv', 'housing_risk_zip.csv']

df = reduce(lambda l,r: l.merge(r, on='zip'), [pd.read_csv(f) for f in files])

---

你可以用reduce减少写作。只需指定一个文件列表，然后就可以合并它们，这样，如果需要添加文件，只需修改文件列表即可

from functools import reduce
import pandas as pd

files = ['econ_risk_zip.csv', 'food_risk_zip.csv',
         'health_risk_zip.csv', 'housing_risk_zip.csv']

df = reduce(lambda l,r: l.merge(r, on='zip'), [pd.read_csv(f) for f in files])