pandas generates wide table from single entry data set

demand

Scenes

A large amount of physical examination data is derived from the hospital database, but in the physical examination data table, each row represents the result of a certain physical examination of a certain person. The purpose is to store each physical examination result of each person as a row, and each column is a physical examination item.

Example

Raw data

	StuID	Type	on one
0	111021	Math	89
1	111021	English	93
2	312983	English	91
3	314621	English	82
4	314621	Math	92
5	112341	Math	82

Purpose: Convert into the following table

	StuID	English	Math
0	111021	93	89
1	312983	91	NaN
2	314621	82	92
3	112341	NaN	82

Option One

• The specific code is as follows

#将’B'列的类别调整为行。
#1
num = df[~df.duplicated(subset=['StuID'])].loc[:,'StuID'].to_list()
#2
result_df = pd.DataFrame({
    
    'StuID': np.array(num)},columns=['StuID','English','Math'])
#3
for i in df.index:
    t = df.loc[i,'Type']
    num = df.loc[i,'StuID']
    result_df.loc[result_df['StuID'] == num,[t]] = df.loc[i,'Num']
print(result_df)

• result