DESCRIPTION
The code fetches annual income statement data for a list of ticker symbols using the Alpha Vantage API. It saves the data as CSV files in a specified folder.
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Importing Required Libraries: The code begins by importing necessary libraries, including `TimeSeries` from `alpha_vantage.timeseries`, `time`, `requests`, `json`, `json_normalize` from `pandas`, and `pd` from `pandas`.
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Reading Ticker Symbols from a CSV File: The script reads ticker symbols from a CSV file named 'TickerFile.csv' using the `pd.read_csv()` function. The ticker symbols are stored in a pandas DataFrame called `df1`.
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Extracting Ticker Symbols: The code retrieves the ticker symbols from the 'Ticker' column of `df1` using `df1['Ticker'].to_numpy()`. The symbols are stored in a numpy array called `list_of_tickers`.
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Setting API Key and Output Path: The user needs to provide their Alpha Vantage API key, which is stored in the variable `key`. The user also needs to specify the folder path where the output CSV files will be saved. The path is stored in the variable `pathway`.
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Defining the 'earnings' Function: The script defines a function named `earnings` that takes the API key, list of tickers, and output path as inputs.
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Initializing Variables: The function initializes a counter variable `i` to keep track of the ticker being processed. An empty DataFrame `df2` is created to store the combined data.
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Fetching Data for Each Ticker: The function iterates over each ticker in the `list_of_tickers` using a `for` loop. It constructs the API URL for fetching income statement data by replacing the ticker symbol and API key in the URL template.
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Handling Rate Limiting: To avoid exceeding the API rate limit, the function checks if the counter `i` is a multiple of 4 (you may adjust this number as per your API's rate limits). If it is a multiple, the script prints "waiting ..." and sleeps for 60 seconds using `time.sleep(60)`.
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Processing the API Response: The function checks if the response dictionary contains the key 'annualReports' using `response_dict['annualReports']`. If the key is not found, the script prints "Didn't save data" for the ticker and continues to the next ticker using `continue`.
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Converting Data to DataFrame: If 'annualReports' key exists, the function creates a DataFrame `df` from the 'annualReports' data extracted from the response dictionary.
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Saving Data as CSV:
- The function saves the DataFrame as a CSV file in the specified output folder -
Executing the Function: The `earnings()` function is called with the API key, list of tickers, and output path provided as arguments.
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The code is then run on the web through the streamlit community cloud @ https://sehaj-finance-data.streamlit.app/