如何为Pandas DataFrame的索引列（v1股票代码列）添加表头？

Great question! The issue you're seeing is that your DataFrame's index (the stock symbols from your v1 list) doesn't have a name assigned. That's why the first column shows up without a header in your output. Let's walk through two straightforward ways to add the "v1" header you want:

Method 1: Set the Index Name When Creating the DataFrame #

You can define the index name right when you initialize your DataFrame using pd.Index() to wrap your v1 list and assign a name to it. Here's how to modify that line of code:

# Replace this line:
# df = pd.DataFrame(index = v1, columns = metric)

# With this:
df = pd.DataFrame(index=pd.Index(v1, name='v1'), columns=metric)

Method 2: Assign the Index Name After Data Scraping #

If you prefer to keep your initial DataFrame setup as-is, you can add a single line after running your scraping function to name the index:

df = get_fundamental_data(df)
# Add this line right here:
df.index.name = 'v1'
print(df)

Either of these methods will make your output match your desired result. Here's what the printed DataFrame will look like:

Sales  Income
v1                    
AAPL  365.82B  94.68B
MSFT  184.90B  71.19B
TSLA   53.82B   5.52B
FB    112.33B  40.30B

Bonus: If You Want "v1" as a Regular Column (Not an Index) #

If you'd rather have the stock symbols as a standard column instead of the index, you can use reset_index() to convert the index to a column and rename it:

df = df.reset_index().rename(columns={'index': 'v1'})
print(df)

This will give you output like this:

v1    Sales  Income
0  AAPL  365.82B  94.68B
1  MSFT  184.90B  71.19B
2  TSLA   53.82B   5.52B
3    FB  112.33B  40.30B

Full Modified Code (Using Method 1) #

Here's the complete code with the index name set during DataFrame creation:

import pandas as pd
from bs4 import BeautifulSoup as bs
import requests
import numpy as np

# For custom list of stocks, edit this list below, otherwise leave commented out
v1 = ['AAPL','MSFT','TSLA','FB','BRK-B','TSM','NVDA','V','JNJ','JPM','WMT','PG','BAC','HD','BABA','TM','XOM','PFE','DIS','KO']

# Header required to scrape from Finviz
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36', 'Upgrade-Insecure-Requests': '1', 'Cookie': 'v2=1495343816.182.19.234.142', 'Accept-Encoding': 'gzip, deflate, sdch', 'Referer': "http://finviz.com/quote.ashx?t="}

# This function is what is used to find the metric of interest and return it
def fundamental_metric(soup, metric):
    return soup.find(text=metric).find_next(class_='snapshot-td2').text

# This function iterates through the index of the data frame (stock_list) and uses the fundemental_metric functinon to find the metric on Finviz for that stock
# Any stock in the list that cannot be scraped will return an error before moving on to the next stock
def get_fundamental_data(df):
    for symbol in df.index:
        try:
            r = requests.get("http://finviz.com/quote.ashx?t="+ symbol.lower(),headers=headers)
            soup = bs(r.content,'html.parser')
            for m in df.columns:
                output = fundamental_metric(soup,m)
                df.loc[symbol,m] = output
            df.replace(['-'], np.NaN)
        except Exception as e:
            print (symbol, 'Not Found')
            print(e)
    return df

# List of metrics to scrape
# Before adding any metrics, ensure the metric being added is available on Finviz and the name is matched identically
metric = ['Sales','Income']
# Set index name when creating DataFrame
df = pd.DataFrame(index=pd.Index(v1, name='v1'), columns=metric)
df = get_fundamental_data(df)
print(df)

内容的提问来源于stack exchange，提问作者J R