Create a new dataframe based on rows with a certain value

Question

I have a large dataframe of transactions which I want to break into two smaller dataframes based on a certain column ("Type"). If "Type" is "S" then add that entire row to the "cust_sell" dataframe, and if "Type" is "P" to the "cust_buy" dataframe. I am using a for loop, but this is only adding the index value to the dataframe. Any help is appreciated!

from win32com.shell import shell, shellcon
import pandas as pd

filename = (shell.SHGetFolderPath(0, shellcon.CSIDL_PERSONAL, None, 0)) + '\MSRB T-1_test.xlsx'
wb = pd.read_excel(filename, sheet_name='T1-20062017', index_col=0, header=0)
cust_buy = []
cust_sell = []

# Create a list of customer buys and sells separately
for i in wb.index:
    if wb['Type'][i] == 'S':
        cust_sell.append([i])
    elif wb['Type'][i] == 'P':
        cust_buy.append([i])

Answer 1

You do not need to write loops. You can do it easily with pandas.

Assuming your dataframe looks like this:

import pandas as pd  

mainDf = pd.DataFrame()
mainDf['Type'] = ['S', 'S', 'S', 'P', 'P', 'S', 'P', 'S']
mainDf['Dummy'] = [1, 2, 3, 4, 5, 6, 7, 8]

To create dataframe for S and P types, you can just do this:

cust_sell = mainDf[mainDf.Type == 'S']
cust_buy = mainDf[mainDf.Type == 'P']

cust_sell output:

  Type  Dummy
0    S      1
1    S      2
2    S      3
5    S      6
7    S      8

cust_buy output:

  Type  Dummy
3    P      4
4    P      5
6    P      7