I have the following code below which reads in csv and cleans them for 5 different financial assets. The code seems repetitive and inefficient. Is there a way I can do this in a loop instead of having to declare the 5 assets variables one-by-one?
import pandas as pd
# Input symbols
stock_symbol = "VTI"
ltb_symbol = "TLT"
stb_symbol = "IEI"
gld_symbol = "GLD"
comms_symbol = "DBC"
session_type = "open" # open, high, low or close
# Read csv for all symbols in Dataframes
stock_df = pd.read_csv("BATS_{}, 1D.csv".format(stock_symbol))
ltb_df = pd.read_csv("BATS_{}, 1D.csv".format(ltb_symbol))
stb_df = pd.read_csv("BATS_{}, 1D.csv".format(stb_symbol))
gld_df = pd.read_csv("BATS_{}, 1D.csv".format(gld_symbol))
comms_df = pd.read_csv("BATS_{}, 1D.csv".format(comms_symbol))
#Clean Dataframes
stock_df = stock_df.rename({'{}'.format(session_type): '{}'.format(stock_symbol)}, axis=1)\
.loc[:,['time','{}'.format(stock_symbol)]]
ltb_df = ltb_df.rename({'{}'.format(session_type): '{}'.format(ltb_symbol)}, axis=1)\
.loc[:,['time','{}'.format(ltb_symbol)]]
stb_df = stb_df.rename({'{}'.format(session_type): '{}'.format(stb_symbol)}, axis=1)\
.loc[:,['time','{}'.format(stb_symbol)]]
gld_df = gld_df.rename({'{}'.format(session_type): '{}'.format(gld_symbol)}, axis=1)\
.loc[:,['time','{}'.format(gld_symbol)]]
comms_df = comms_df.rename({'{}'.format(session_type): '{}'.format(comms_symbol)}, axis=1)\
.loc[:,['time','{}'.format(comms_symbol)]]
Create dictionary of DataFrames:
symbols = [stock_symbol,ltb_symbol,stb_symbol,gld_symbol,comms_symbol]
session_type = "open" # open, high, low or close
# Read csv for all symbols in Dataframes
dfs = {s: pd.read_csv("BATS_{}, 1D.csv".format(s)).rename({'{}'.format(session_type): '{}'.format(stock_symbol)}, axis=1).loc[:,['time','{}'.format(stock_symbol)]] for s in symbols}
You can also filter only 2 columns in read_csv by usecols parameter:
dfs = {s: pd.read_csv("BATS_{}, 1D.csv".format(s), usecols=['time',session_type]).rename({session_type: stock_symbol}, axis=1) for s in symbols}
And last is possible for DataFrames select by keys:
print (dfs['VTI'])
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