我想向 df1 添加列，該列使用基于 df1 行的條件從 df2 中查找值。例如：df1Name Date Score CountryJohn 1st Jan 5 USJohn 2nd Jan 6 USPhil 1st Jan 4 CanadaPhil 2nd Jan 8 CanadaPhil 3rd Jan 7 Canada如果 Name =John，Date is > 1st of Jan 并且 country 是 = US，我想要一個公式來查找 df2 中另一列的值。所有其他行都相同。
1 回答
神不在的星期二
TA貢獻1963條經(jīng)驗 獲得超6個贊
嘗試這個...
import pandas as pd
import numpy as np
columns = ["Name","Date","Score","Country"]
data=[
["John","1st Jan","5","US"],
["John","2nd Jan","6","US"],
["Phil","1st Jan","4","Canada"],
["Phil","2nd Jan","8","Canada"],
["Phil","3rd Jan","7","Canada"]
]
columns2 = ["Col1","Col2","Col3","Col4"]
data2 = [[1,2,3,4],[1,2,3,4],[1,2,3,4],[1,2,3,4] ]
df = pd.DataFrame(data, columns = columns)
df2 = pd.DataFrame(data2, columns = columns2)
print(df)
print(df2)
df.loc[(df['Name'] == "John") &
(df['Date'] == "1st Jan")&
(df['Score'] == "5") &
(df['Country'] == "US"), 'New'] = df2["Col1"]
name = "Phil"
date = "1st Jan"
score = "4"
country = "Canada"
df.loc[(df['Name'] == name) &
(df['Date'] == date) &
(df['Score'] == score) &
(df['Country'] == country), 'New'] = df2["Col2"]
輸出：
Name Date Score Country
0 John 1st Jan 5 US
1 John 2nd Jan 6 US
2 Phil 1st Jan 4 Canada
3 Phil 2nd Jan 8 Canada
4 Phil 3rd Jan 7 Canada
Col1 Col2 Col3 Col4
0 1 2 3 4
1 1 2 3 4
2 1 2 3 4
3 1 2 3 4
Name Date Score Country New
0 John 1st Jan 5 US 1.0
1 John 2nd Jan 6 US NaN
2 Phil 1st Jan 4 Canada 2.0
3 Phil 2nd Jan 8 Canada NaN
4 Phil 3rd Jan 7 Canada NaN
編輯
您可以通過使用一個函數(shù)df.apply()和一個調(diào)用該函數(shù)的 lambda 來使其更加自動化。
def lambdafunc(row):
name = row[0]
date = row[1]
score = row[2]
country = row[3]
df.loc[(df['Name'] == name) &
(df['Date'] == date) &
(df['Score'] == score) &
(df['Country'] == country), 'New'] = df2.loc[df2['Col1'] == name, 'Col4']
df.apply(lambda x: lambdafunc(x), axis = 1)
print(df)
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