Free stock prices in python excel export yfinance
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certainly! in this tutorial, we’ll learn how to retrieve free stock price data using the `yfinance` library in python and then export that data to an excel file using the `pandas` library.
prerequisites
make sure you have the following python packages installed:
1. *yfinance* – to fetch stock price data.
2. *pandas* – for data manipulation and exporting to excel.
3. *openpyxl* or *xlsxwriter* – for writing excel files.
you can install these packages using pip:
step-by-step guide
1. **import libraries**: first, we need to import the necessary libraries.
2. **fetch stock data**: use the `yfinance` library to download historical stock data.
3. **process the data**: optionally, you can manipulate the data as needed.
4. **export to excel**: finally, use `pandas` to export the data to an excel file.
example code
here's an example code snippet that demonstrates how to accomplish this:
explanation of the code
1. **import libraries**:
`yfinance` is used to fetch stock data.
`pandas` is used for data manipulation and exporting to excel.
2. **define ticker and date range**:
you can change `ticker` to any stock symbol you want (e.g., 'googl' for alphabet, 'msft' for microsoft).
the `start_date` and `end_date` define the time period for which you want to collect stock data.
3. **fetch stock data**:
`yf.download()` retrieves historical stock data for the specified ticker and date range and returns it as a dataframe.
4. **display data**:
`stock_data.head()` prints the first five rows of the fetched data for a quick overview.
5. **export to excel**:
`to_excel()` method exports the dataframe to an excel file. the file is saved in the current working directory with the name `ticker_stock_data.xlsx`.
running the code
to run the code:
1. copy the script into a python (.py) file or a jupyter notebook.
2. make sure you have an active internet connection since `yfinance` fetches data from the web.
3. e ...
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