当前代码:
import pandas as pd
data = pd.read_csv(r'Data.csv', sep=',', encoding='latin-1')
col = data.loc[data['Customer Code'] == '001']
print(col)
它的作用
这将获得客户代码等于001的所有数据
我怎样才能
我可以怎样做:
111示例
当前数据
Customer Code, Name
001, Customer 1
001, Customer 1
001, Customer 1
002, Customer 2
003, Customer 3
所需数据选择客户代码001的数据
Customer Code, Name
001, Customer 1
001, Customer 1
001, Customer 1
002, Customer 2
003, Customer 3
111, Customer 1 --Pasted from 001, but changed the customer code
111, Customer 1 --Pasted from 001, but changed the customer code
111, Customer 1 --Pasted from 001, but changed the customer code
下面的代码获取预期的输出。 这里，111是通过向现有的customer_code添加110得到的。 这行代码可能会被改变以使用不同的编号方案。
# Import library
import pandas as pd
import numpy as np
# Create DataFrame
df = pd.DataFrame({
'Customer_Code':['001','001', '001', '002', '003'],
'Name': ['Customer 1','Customer 1','Customer 1','Customer 2','Customer 3']
})
# Set counter for new label
counter = 110
# Create new labels
temp = df[['Customer_Code']]
temp['Name'] = df.apply(lambda x: x['Name']+' --Pasted from '+ x['Customer_Code'] + ', but changed the customer code', axis=1)
temp['new_code'] = (df['Customer_Code'].astype(int) + counter).astype(str)
temp = temp[['new_code','Name']].rename(columns={'new_code':'Customer_Code'})
# Join new labels to original DataFrame
df = df[['Customer_Code','Name']]
df = pd.concat([df, temp], axis=0)
# Output
print(df)
输出量
注意:name列中的数据是右对齐的，而不是如问题中预期输出所示的左对齐。
Customer_Code Name
0 001 Customer 1
1 001 Customer 1
2 001 Customer 1
3 002 Customer 2
4 003 Customer 3
0 111 Customer 1 --Pasted from 001, but changed the ...
1 111 Customer 1 --Pasted from 001, but changed the ...
2 111 Customer 1 --Pasted from 001, but changed the ...
3 112 Customer 2 --Pasted from 002, but changed the ...
4 113 Customer 3 --Pasted from 003, but changed the ...
