我有2个熊猫系列如下:
indicator_name
1 6-Month Bill Auction
2 7-Year Note Auction
3 ADP Nonfarm Employment Change
4 All Car Sales
5 All Truck Sales
6 API Weekly Crude Oil Stock
7 API Weekly Cushing Crude Oil Stock
8 API Weekly Distillates Stocks
9 API Weekly Gasoline Stock
10 Average Hourly Earnings (MoM)
11 Average Weekly Hours
...
和
indicator_name
1 ADP Employment Change
2 Advance Goods Trade Balance
3 Advance Retail Sales
4 Average Hourly Earnings MoM
5 Average Hourly Earnings YoY
6 Average Weekly Hours All Employees
7 Avg Hourly Earning MOM Prod
8 Avg Hourly Earning YOY Prod
9 Avg Weekly Hours Production
我想将它们组合起来,以便按以下方式按字母顺序对齐:
1 6-Month Bill Auction null
2 7-Year Note Auction null
3 null ADP Employment Change
4 ADP Nonfarm Employment Change Advance Goods Trade Balance
5 null Advance Retail Sales
6 All Car Sales null
7 All Truck Sales null
8 API Weekly Crude Oil Stock null
9 API Weekly Cushing Crude Oil Stock null
10 API Weekly Distillates Stocks null
11 API Weekly Gasoline Stock null
12 Average Hourly Earnings (MoM) Average Hourly Earnings MoM
13 null Average Hourly Earnings YoY
14 Average Weekly Hours Average Weekly Hours All Employees
15 null Avg Hourly Earning MOM Prod
16 null Avg Hourly Earning YOY Prod
17 null Avg Weekly Hours Production
有关如何迅速完成任何建议吗? THX!
答案 0 :(得分:1)
假设您有一个列数据帧。
df = pd.DataFrame({'indicator_name':[
'6-Month Bill Auction',
'7-Year Note Auction',
'ADP Nonfarm Employment Change',
'All Car Sales',
'All Truck Sales',
'API Weekly Crude Oil Stock',
'API Weekly Cushing Crude Oil Stock',
'API Weekly Distillates Stocks',
'API Weekly Gasoline Stock',
'Average Hourly Earnings (MoM)',
'Average Weekly Hours']})
df1 = pd.DataFrame({'indicator_name':[
'ADP Employment Change',
'Advance Goods Trade Balance',
'Advance Retail Sales',
'Average Hourly Earnings MoM',
'Average Hourly Earnings YoY',
'Average Weekly Hours All Employees',
'Avg Hourly Earning MOM Prod',
'Avg Hourly Earning YOY Prod',
'Avg Weekly Hours Production']})
df.set_index('indicator_name', drop=False, inplace=True)
df1.set_index('indicator_name', drop=False, inplace=True)
df1.columns = ['indicator_name2']
pd.concat([df, df1], axis=1).sort_index().reset_index(drop=True)
输出
indicator_name indicator_name2
0 6-Month Bill Auction NaN
1 7-Year Note Auction NaN
2 NaN ADP Employment Change
3 ADP Nonfarm Employment Change NaN
4 API Weekly Crude Oil Stock NaN
5 API Weekly Cushing Crude Oil Stock NaN
6 API Weekly Distillates Stocks NaN
7 API Weekly Gasoline Stock NaN
8 NaN Advance Goods Trade Balance
9 NaN Advance Retail Sales
10 All Car Sales NaN
11 All Truck Sales NaN
12 Average Hourly Earnings (MoM) NaN
13 NaN Average Hourly Earnings MoM
14 NaN Average Hourly Earnings YoY
15 Average Weekly Hours NaN
16 NaN Average Weekly Hours All Employees
17 NaN Avg Hourly Earning MOM Prod
18 NaN Avg Hourly Earning YOY Prod
19 NaN Avg Weekly Hours Production