我输入的东西看起来像DF1(下面要生成的代码),并希望在输出中看起来像DF2。
我们的想法是为每一行找到该行中具有最高值的列名,相应的值,以及该行中具有第二高值的列名,以及其对应的值。
使用pandas有简单的方法吗?
import pandas as pd
DF1 = pd.DataFrame({'User' : pd.Series(["Line1","Line2","Line3", "Line4"], index=['1', '2','3','4']), 'Var1' : pd.Series([9,12,3,21], index=['1', '2','3','4']),'Var2' : pd.Series([8,16,3,2], index=['1', '2','3','4']),'Var3' : pd.Series([7,5,6,9], index=['1', '2','3','4']),'Var4' : pd.Series([10,13,20,20], index=['1', '2','3','4']),'Var5' : pd.Series([8,2,13,1], index=['1', '2','3','4']),'Var6' : pd.Series([4,4,7,11], index=['1', '2','3','4']),'Var7' : pd.Series([15,13,4,7], index=['1', '2','3','4'])})
DF1
DF2 = pd.DataFrame({'User' : pd.Series(["Line1","Line2","Line3", "Line4"], index=['1', '2','3','4']), 'Max1Name' : pd.Series(["Var7","Var2","Var4","Var1"], index=['1', '2','3','4']),'Max1Value' : pd.Series([15,16,20,21], index=['1', '2','3','4']),'Max2Name' : pd.Series(["Var4","Var4","Var5","Var4"], index=['1', '2','3','4']),'Max2Value' : pd.Series([10,13,13,20], index=['1', '2','3','4'])})
DF2
答案 0 :(得分:4)
不确定这是否是最简单的方法,但您可以这样做:
def top(x):
x.set_index('User', inplace=True)
df = pd.DataFrame({'Max1Name':[],'Max2Name':[],'Max1Value':[],'Max2Value':[]})
df.index.name='User'
df.loc[x.index.values[0],['Max1Name', 'Max2Name']] = x.sum().nlargest(2).index.tolist()
df.loc[x.index.values[0],['Max1Value', 'Max2Value']] = x.sum().nlargest(2).values
return df
DF1.groupby('User').apply(top).reset_index(level=1, drop=True).reset_index()
产生所需的输出:
User Max1Name Max1Value Max2Name Max2Value
0 Line1 Var7 15 Var4 10
1 Line2 Var2 16 Var4 13
2 Line3 Var4 20 Var5 13
3 Line4 Var1 21 Var4 20
更简单的方法是:
DF1.groupby('User').apply(lambda x: x.set_index('User').sum().nlargest(2))
用户可以获得前2名:
User
Line1 Var7 15
Var4 10
Line2 Var2 16
Var4 13
Line3 Var4 20
Var5 13
Line4 Var1 21
Var4 20
dtype: int64