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Reproducible Example

import pandas as pd
import yfinance as yf
from datetime import date, timedelta

end_date= date.today().strftime("%Y-%m-%d")
start_date= (date.today() - timedelta(days= 365)).strftime("%Y-%m-%d")

tickers= ['RELIANCE.NS', 'TCS.NS', 'INFY.NS', 'HDFCBANK.NS']

data= yf.download(tickers, start= start_date, end= end_date)

data= data.reset_index()

data_melted= data.melt(id_vars= ['Date'], var_name= ['Attribute', 'Ticker'])

Issue Description

KeyError Traceback (most recent call last)
Cell In [19], line 15
11 data= data.reset_index()
13 # melt the DataFrame to make it long format where each row is a
14 # unique combination of Date, Ticker, and attributes
---> 15 data_melted= data.melt(id_vars= ['Date'], var_name= ['Attribute', 'Ticker'])
17 # pivot the melted DataFrame to have the attributes (Open, High, Low, etc.) as columns
18 data_pivoted= data_melted.pivot_table(index= ['Date', 'Ticker'],
19 columns= 'Attribute', values= 'value',
20 aggfunc= 'first')

File ~/python_3.9.0/lib/python3.9/site-packages/pandas/core/frame.py:9942, in DataFrame.melt(self, id_vars, value_vars, var_name, value_name, col_level, ignore_index)
9932 @appender(_shared_docs["melt"] % {"caller": "df.melt(", "other": "melt"})
9933 def melt(
9934 self,
(...)
9940 ignore_index: bool = True,
9941 ) -> DataFrame:
-> 9942 return melt(
9943 self,
9944 id_vars=id_vars,
9945 value_vars=value_vars,
9946 var_name=var_name,
9947 value_name=value_name,
...
77 )
78 if value_vars_was_not_none:
79 frame = frame.iloc[:, algos.unique(idx)]

KeyError: "The following id_vars or value_vars are not present in the DataFrame: ['Date']"

Expected Behavior

The melt function should generate a DataFrame to make it long format where each row is a unique combination of Date, Ticker, and attributes

Installed Versions