Feb-12-2020, 05:46 PM
Hi,
I have dataframe:
df3:
if name & value exist in df3, the replace data corresponding row value with row value in df3.
exampe, A &t1 exist, its value is 0 in df3.
final desired output:
I have dataframe:
df3:
name type score combined A t1 0 A_t1 B t2 0 B_t2 C t2 1 C_t2 A t2 1 A_t2 C t1 0 C_t1 B t3 0 B_t3summary_table:
name t1 t2 t3 A na na na B na na na C na na naI loop through rows summary_table (A,B,C) & columns (t1,t2,t3)
if name & value exist in df3, the replace data corresponding row value with row value in df3.
exampe, A &t1 exist, its value is 0 in df3.
final desired output:
name t1 t2 t3 A 0 1 na B na 0 0 C 0 1 naI use the below code, but I am not getting the output.
import pandas as pd import numpy as np myrws=sorted(list(data1.name.unique())) mycols=sorted(list(data1.category.unique())) lenrows=len(myrws) for i in range(1,len(myrws)): c1=myrws[i] print(myrws[i]) print("-"*10) for j in range(1,len(mycols)): print(1,j) print(mycols[j]) r1=mycols[j] tmp=c1+"_"+r1 print("tmp:",tmp) idx=(df3[df3['combined']==tmp].index.values) if idx: print('matched-----') summary_table.loc[i,j]=df3.iloc[idx,3] else: print('nottt matched')