[英]Map two dataframes using pandas - python
Have two dataframes有两个数据框
import pandas as pd
df1 = pd.DataFrame([['tom', 2, 11111]], columns=["name", "cell", "marks"])
df2 = pd.DataFrame([['tomm', 2, 11111, 2548],
['matt', 2, 158416, 2483],
['tonmmm', 2, 11111, 2549]
], columns=["name", "cell", "marks", "passwd"])
Input输入
df1 df1
name cell marks
0 tom 2 11111
df2 df2
name cell marks passwd
0 tomm 2 11111 2548
1 matt 2 158416 2483
2 tonmmm 2 11111 2549
map two dataframe which has similar columns map 两个 dataframe 具有相似的列
get columns from df2 which has match atleast a count of 2. here cell
and marks
matches with df1 with 2 values从 df2 中获取至少匹配计数为 2 的列。此处
cell
和marks
与 df1 匹配,具有 2 个值
expected output:预期 output:
name cell marks passwd
0 tomm 2 11111 2548
1 tonmmm 2 11111 2549
You could try this:你可以试试这个:
df1 = pd.DataFrame([['tom', 2, 11111]], columns=["name", "cell", "marks"])
df2 = pd.DataFrame([['tomm', 2, 11111, 2548],
['matt', 2, 158416, 2483],
['tonmmm', 2, 11111, 2549]
], columns=["name", "cell", "marks", "passwd"])
temp=[len([i for i in list(row)[1:] if i in list(df1.iloc[0,:])])>=2 for row in df2[df2.columns[:len(df2.columns)-1]].to_records()]
newdf=df2[temp]
print(newdf)
Output: Output:
name cell marks passwd
0 tomm 2 11111 2548
2 tonmmm 2 11111 2549
Edit : In the case you want to sort it base on the number of matches, you could try:编辑:如果您想根据匹配数对其进行排序,您可以尝试:
import pandas as pd
import numpy as np
df1 = pd.DataFrame([['tom', 2, 11111]], columns=["name", "cell", "marks"])
df2 = pd.DataFrame([['tomm', 2, 11111, 2548],['matt', 2, 158416, 2483], ['tom', 2, 11111, 2549]], columns=["name", "cell", "marks", "passwd"])
temp=[len([i for i in list(row)[1:] if i in list(df1.iloc[0,:])]) for row in df2[df2.columns[:len(df2.columns)-1]].to_records()]
newdf=df2.copy().assign(val=temp).sort_values(by='val',ascending=False)
mask=np.where(newdf.val.ge(2), True, False)
newdf=newdf.drop(['val'],axis=1).reset_index(drop=True)[mask]
print(newdf)
Output: Output:
name cell marks passwd
0 tom 2 11111 2549
1 tomm 2 11111 2548
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