Sep-03-2021, 03:38 AM
Thanks for the hint. I was able to solve the problem using pandas join function.
import pandas as pd from yahoo_fin import stock_info as si ti = pd.read_csv('/Users/detlefschmitt/Desktop/TickerList.csv') stock_list = ti["Ticker"].tolist() stats1 = {} stats2 = {} for ticker in stock_list: data = si.get_stats(ticker) stats1[ticker] = data for ticker in stock_list: data = si.get_stats_valuation(ticker) stats2[ticker] = data combined1 = pd.concat(stats1) combined1 = combined1.reset_index() del combined1["level_1"] combined1.columns = ["Ticker", "Attribute", "Recent"] combined2 = pd.concat(stats2) combined2 = combined2.reset_index() del combined2["level_1"] combined2.columns = ["Ticker", "Attribute", "Recent"] df1 = pd.DataFrame(combined1) df2 = pd.DataFrame(combined2) df11 = df1.pivot(index='Ticker', columns='Attribute', values='Recent') df22 = df2.pivot(index='Ticker', columns='Attribute', values='Recent') df3 = df11.join(df22) df3.to_csv(r'/Users/detlefschmitt/Desktop/stats.csv')The screenshot in the attachment illustrates what I was trying to achieve. I had df11 and df22 and tried to join them to get df3.