Hello python gurus,
I am trying to concatenate multiple data frames but when I run the application it gives me this error:
KeyError: 'Level Date must be same as name (None)'
I am following this tutorial: Python for finance
The tutorial's way of joining the csv files generates a combined csv file with all the stocks but gives a new column for each stock (500). Ideally I just want one column called "Tickers" not 500. So I am trying melt instead of outer join but not getting it to work.
Full code is here: https://codeshare.io/amDv7o
I am trying to concatenate multiple data frames but when I run the application it gives me this error:
KeyError: 'Level Date must be same as name (None)'
I am following this tutorial: Python for finance
The tutorial's way of joining the csv files generates a combined csv file with all the stocks but gives a new column for each stock (500). Ideally I just want one column called "Tickers" not 500. So I am trying melt instead of outer join but not getting it to work.
Full code is here: https://codeshare.io/amDv7o
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def compile_data(): with open("sp500tickers.pickle", "rb") as f: tickers = Cpickle.load(f) main_df = pd.DataFrame() for count, ticker in enumerate(tickers): df = pd.read_csv('stock_dfs/{}.csv'.format(ticker)) df.reset_index('Date', inplace=True) df.rename(columns={'Adj Close': ticker}, inplace=True) df.drop(['Open', 'High', 'Low', 'Close', 'Volume'], 1, inplace=True) if main_df.empty: main_df = df else: main_df = main_df.melt(id_vars=['Date'], var_name='Ticker', value_name='Closed') if count % 10 == 0: print(count) print(main_df.head()) main_df.to_csv('sp500_joined_closes.csv')compile_data() |
