Hey there! Let's fix this up so you get that clean DataFrame you're after. The key here is to collect the valid ticker-marketCap pairs as you iterate instead of just printing them, then convert that collection into a DataFrame. Here's how to adjust your code:

First, let's put all the pieces together (including your existing ticker-reading code):

import pandas as pd
from pandas_datareader import data as pdr
import yfinance as yf

# Step 1: Read tickers from your text file
with open("/Users/AB/OD/Earnings/tickers.txt") as fh:
    tick1 = fh.read().split()

# Step 2: Initialize an empty list to store valid data
valid_data = []

# Step 3: Iterate through tickers, collect market cap data
for ticker in tick1:
    try:
        # Extract the numeric market cap value (get_quote_yahoo returns a Series, so we grab the first element)
        market_cap = pdr.get_quote_yahoo(ticker)['marketCap'].iloc[0]
        # Add the ticker and its market cap to our list as a tuple
        valid_data.append( (ticker, market_cap) )
    except Exception as e:
        # Optional: Print failed tickers for debugging (remove if not needed)
        print(f"Skipping {ticker}: Could not retrieve market cap. Error: {str(e)}")
        pass

# Step 4: Convert the collected data to your target DataFrame
market_cap_df = pd.DataFrame(valid_data, columns=['ticker', 'marketCap'])

# Preview the result
print(market_cap_df)

What's improved here? #

• We use a valid_data list to store only successful (ticker, marketCap) pairs—this filters out any tickers that fail to return data automatically.
• Added .iloc[0] to pull the actual numeric value from the Series returned by get_quote_yahoo—without this, your DataFrame would store Series objects instead of plain numbers.
• Included an optional debug print to see which tickers are failing (helpful if you need to troubleshoot missing data).
• Explicitly set the DataFrame column names to match your required ticker and marketCap headers.

This should give you a tidy, usable DataFrame with exactly the data you need. 😊

内容的提问来源于stack exchange，提问作者ABe