[英]Concatenating two DataFrames but only for common values in Python
I have 2 dataframes like this:我有 2 个这样的数据框:
name code phone_number
Joe BX13 03453
Bill C308 321356
Donald H314 34532
Mike J4D6 2134
code vehicle
C308 Mercedes
H314 BMW
I would like to concatenate them but only for common values in a specific column so it would look like this:我想将它们连接起来,但仅限于特定列中的公共值,因此它看起来像这样:
name code vehicle
Bill C308 Mercedes
Donald H314 BMW
df3=pd.concat([df1, df2])
looks promising but I don't know to specify that I only want the common values.看起来很有希望,但我不知道要指定我只想要共同的价值观。 What arguments should I put in the parenthesis?
我应该在括号中输入什么 arguments?
I suppose you are looking for pd.merge.我想您正在寻找 pd.merge。
df2=pd.merge(df2,df1,on="code",how="inner").drop(columns="phone_number")
df1 is the data with name code phone_number
columns df2 is the data with code vehicle
columns df1 是
name code phone_number
列的数据 df2 是code vehicle
列的数据
You can use df.merge
你可以使用
df.merge
Setting up your data设置您的数据
import pandas as pd
import io
t = '''
name,code,phone_number
Joe,BX13,3453
Bill,C308,321356
Donald,H314,34532
Mike,J4D6,2134'''
df1 = pd.read_csv(io.StringIO(t))
t = '''
code,vehicle
C308,Mercedes
H314,BMW'''
df2 = pd.read_csv(io.StringIO(t))
Now you can merge the two dataframes with selected columns现在您可以将两个数据框与选定的列合并
df1[['name','code']].merge(df2, on='code', how='inner')
Out:出去:
name code vehicle
0 Bill C308 Mercedes
1 Donald H314 BMW
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