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Compare multiple tickers income
This commit is contained in:
didier
@@ -11,6 +11,7 @@ from gamestonk_terminal import feature_flags as gtff
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from gamestonk_terminal import config_terminal as cfg
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from gamestonk_terminal.helper_funcs import get_flair, parse_known_args_and_warn
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from gamestonk_terminal.comparison_analysis import yahoo_finance_api as yf_api
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from gamestonk_terminal.comparison_analysis import market_watch_api as mw_api
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from gamestonk_terminal.menu import session
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from prompt_toolkit.completion import NestedCompleter
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@@ -27,6 +28,7 @@ class ComparisonAnalysisController:
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"select",
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"historical",
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"corr",
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"income",
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]
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def __init__(
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@@ -77,6 +79,8 @@ class ComparisonAnalysisController:
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print(" historical historical data comparison")
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print(" corr correlation between similar companies")
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print("")
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print(" income income financials comparison")
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print("")
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return
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@staticmethod
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@@ -193,6 +197,10 @@ class ComparisonAnalysisController:
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other_args, self.stock, self.ticker, self.start, self.interval, self.similar
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)
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def call_income(self, other_args: List[str]):
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"""Process income command"""
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mw_api.compare_income(other_args, self.ticker, self.similar)
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def menu(stock: pd.DataFrame, ticker: str, start: datetime, interval: str):
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"""Comparison Analysis Menu"""
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429
gamestonk_terminal/comparison_analysis/market_watch_api.py
Normal file
429
gamestonk_terminal/comparison_analysis/market_watch_api.py
Normal file
@@ -0,0 +1,429 @@
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""" Comparison Analysis Market Watch View """
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__docformat__ = "numpy"
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import argparse
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import requests
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import pandas as pd
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from bs4 import BeautifulSoup
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from typing import List, Dict, Tuple
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from gamestonk_terminal.helper_funcs import (
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get_user_agent,
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parse_known_args_and_warn,
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patch_pandas_text_adjustment,
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financials_colored_values,
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)
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from gamestonk_terminal import feature_flags as gtff
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def compare_income(other_args: List[str], ticker: str, similar: List[str]):
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"""Compare income between companies
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Parameters
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----------
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other_args : List[str]
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Command line arguments to be processed with argparse
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ticker : str
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Main ticker to compare income
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similar : List[str]
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Similar companies to compare income with
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"""
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parser = argparse.ArgumentParser(
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add_help=False,
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prog="income",
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description="""
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Prints either yearly or quarterly income statement the company, and compares
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it against similar companies. [Source: Market Watch]
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""",
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)
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parser.add_argument(
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"-s",
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"--similar",
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dest="l_similar",
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type=lambda s: [str(item) for item in s.split(",")],
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default=[],
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help="similar companies to compare with.",
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)
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parser.add_argument(
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"-a",
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"--also",
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dest="l_also",
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type=lambda s: [str(item) for item in s.split(",")],
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default=[],
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help="apart from loaded similar companies also compare with.",
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)
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parser.add_argument(
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"-q",
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"--quarter",
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action="store_true",
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default=False,
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dest="b_quarter",
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help="Quarter financial data flag.",
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)
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parser.add_argument(
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"-t",
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"--timeframe",
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dest="s_timeframe",
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type=str,
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default=None,
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help="Specify yearly/quarterly timeframe. Default is last.",
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)
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try:
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ns_parser = parse_known_args_and_warn(parser, other_args)
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if not ns_parser:
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return
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if ns_parser.l_similar:
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similar = ns_parser.l_similar
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similar += ns_parser.l_also
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# Add main ticker to similar list of companies
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similar.insert(0, ticker)
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l_timeframes, ddf_financials = prepare_comparison_financials(
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similar, "income", ns_parser.b_quarter
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)
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if ns_parser.s_timeframe:
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if ns_parser.s_timeframe not in l_timeframes:
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raise ValueError(
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f"Timeframe {ns_parser.s_timeframe} should be one of {l_timeframes}"
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)
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s_timeframe = ns_parser.s_timeframe
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else:
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s_timeframe = l_timeframes[-1]
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df_financials_compared = combine_similar_financials(
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ddf_financials, similar, s_timeframe
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)
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if gtff.USE_COLOR:
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df_financials_compared = df_financials_compared.applymap(
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financials_colored_values
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)
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patch_pandas_text_adjustment()
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pd.set_option("display.max_colwidth", None)
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pd.set_option("display.max_rows", None)
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df_financials_compared.index.name = s_timeframe
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print(df_financials_compared.to_string())
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print("")
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except Exception as e:
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print(e)
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print("")
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return
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def balance(l_args, s_ticker):
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parser = argparse.ArgumentParser(
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add_help=False,
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prog="balance",
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description="""
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Prints either yearly or quarterly assets from balance sheet of the company.
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The following fields are expected: Cash & Short Term Investments, Cash & Short Term
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Investments Growth, Cash Only, Short-Term Investments, Cash & ST Investments / Total
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Assets, Total Accounts Receivable, Total Accounts Receivable Growth, Accounts
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Receivables, Net, Accounts Receivables, Gross, Bad Debt/Doubtful Accounts, Other
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Receivable, Accounts Receivable Turnover, Inventories, Finished Goods, Work in
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Progress, Raw Materials, Progress Payments & Other, Other Current Assets,
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Miscellaneous Current Assets, Net Property, Plant & Equipment, Property, Plant &
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Equipment - Gross, Buildings, Land & Improvements, Computer Software and Equipment,
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Other Property, Plant & Equipment, Accumulated Depreciation, Total Investments and
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Advances, Other Long-Term Investments, Long-Term Note Receivables, Intangible Assets,
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Net Goodwill, Net Other Intangibles, Other Assets.
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Prints either yearly or quarterly liabilities and shareholders' equity from balance
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sheet of the company. The following fields are expected: ST Debt & Current Portion LT
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Debt, Short Term Debt, Current Portion of Long Term Debt, Accounts Payable, Accounts
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Payable Growth, Income Tax Payable, Other Current Liabilities, Dividends Payable,
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Accrued Payroll, Miscellaneous Current Liabilities, Long-Term Debt, Long-Term Debt
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excl. Capitalized Leases, Non-Convertible Debt, Convertible Debt, Capitalized Lease
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Obligations, Provision for Risks & Charges, Deferred Taxes, Deferred Taxes - Credits,
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Deferred Taxes - Debit, Other Liabilities, Other Liabilities (excl. Deferred Income),
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Deferred Income, Non-Equity Reserves, Total Liabilities / Total Assets, Preferred Stock
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(Carrying Value), Redeemable Preferred Stock, Non-Redeemable Preferred Stock, Common
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Equity (Total), Common Equity/Total Assets, Common Stock Par/Carry Value, Retained
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Earnings, ESOP Debt Guarantee, Cumulative Translation Adjustment/Unrealized For. Exch.
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Gain, Unrealized Gain/Loss Marketable Securities, Revaluation Reserves, Treasury Stock,
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Total Shareholders' Equity, Total Shareholders' Equity / Total Assets, Accumulated
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Minority Interest, Total Equity, Total Current Assets, Total Assets, Total Current
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Liabilities, Total Liabilities, and Liabilities & Shareholders' Equity.
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[Source: Market Watch]
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""",
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)
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parser.add_argument(
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"-q",
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"--quarter",
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action="store_true",
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default=False,
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dest="b_quarter",
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help="Quarter fundamental data flag.",
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)
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try:
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ns_parser = parse_known_args_and_warn(parser, l_args)
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if not ns_parser:
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return
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df_financials = prepare_df_financials(s_ticker, "balance", ns_parser.b_quarter)
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if gtff.USE_COLOR:
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df_financials = df_financials.applymap(financials_colored_values)
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patch_pandas_text_adjustment()
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pd.set_option("display.max_colwidth", None)
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pd.set_option("display.max_rows", None)
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print(df_financials.to_string(index=False))
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print("")
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except Exception as e:
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print(e)
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print("")
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return
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def cash(l_args, s_ticker):
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parser = argparse.ArgumentParser(
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add_help=False,
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prog="cash_flow",
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description="""
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Prints either yearly or quarterly cash flow operating activities of the company.
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The following fields are expected: Net Income before Extraordinaries, Net Income
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Growth, Depreciation, Depletion & Amortization, Depreciation and Depletion,
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Amortization of Intangible Assets, Deferred Taxes & Investment Tax Credit, Deferred
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Taxes, Investment Tax Credit, Other Funds, Funds from Operations, Extraordinaries,
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Changes in Working Capital, Receivables, Accounts Payable, Other Assets/Liabilities,
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and Net Operating Cash Flow Growth.
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Prints either yearly or quarterly cash flow investing activities of the company.
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The following fields are expected: Capital Expenditures, Capital Expenditures Growth,
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Capital Expenditures/Sales, Capital Expenditures (Fixed Assets), Capital Expenditures
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(Other Assets), Net Assets from Acquisitions, Sale of Fixed Assets & Businesses,
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Purchase/Sale of Investments, Purchase of Investments, Sale/Maturity of Investments,
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Other Uses, Other Sources, Net Investing Cash Flow Growth.
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Prints either yearly or quarterly cash flow financing activities of the company.
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The following fields are expected: Cash Dividends Paid - Total, Common Dividends,
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Preferred Dividends, Change in Capital Stock, Repurchase of Common & Preferred Stk.,
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Sale of Common & Preferred Stock, Proceeds from Stock Options, Other Proceeds from Sale
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of Stock, Issuance/Reduction of Debt, Net, Change in Current Debt, Change in Long-Term
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Debt, Issuance of Long-Term Debt, Reduction in Long-Term Debt, Other Funds, Other Uses,
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Other Sources, Net Financing Cash Flow Growth, Net Financing Cash Flow/Sales, Exchange
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Rate Effect, Miscellaneous Funds, Net Change in Cash, Free Cash Flow, Free Cash Flow
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Growth, Free Cash Flow Yield, Net Operating Cash Flow, Net Investing Cash Flow, Net
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Financing Cash Flow.
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[Source: Market Watch]
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""",
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)
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parser.add_argument(
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"-q",
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"--quarter",
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action="store_true",
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default=False,
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dest="b_quarter",
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help="Quarter fundamental data flag.",
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)
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try:
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ns_parser = parse_known_args_and_warn(parser, l_args)
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if not ns_parser:
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return
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df_financials = prepare_df_financials(s_ticker, "cashflow", ns_parser.b_quarter)
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if gtff.USE_COLOR:
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df_financials = df_financials.applymap(financials_colored_values)
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patch_pandas_text_adjustment()
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pd.set_option("display.max_colwidth", None)
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pd.set_option("display.max_rows", None)
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print(df_financials.to_string(index=False))
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print("")
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except Exception as e:
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print(e)
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print("")
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return
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def prepare_df_financials(
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ticker: str, statement: str, quarter: bool = False
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) -> pd.DataFrame:
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"""Builds a DataFrame with financial statements for a given company
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Parameters
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----------
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ticker : str
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Company's stock ticker
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statement : str
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Either income, balance or cashflow
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quarter : bool, optional
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Return quarterly financial statements instead of annual, by default False
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Returns
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-------
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pd.DataFrame
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A DataFrame with financial info
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Raises
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------
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ValueError
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If statement is not income, balance or cashflow
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"""
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financial_urls = {
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"income": {
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"quarter": "https://www.marketwatch.com/investing/stock/{}/financials/income/quarter",
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"annual": "https://www.marketwatch.com/investing/stock/{}/financials/income",
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},
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"balance": {
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"quarter": "https://www.marketwatch.com/investing/stock/{}/financials/balance-sheet/quarter",
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"annual": "https://www.marketwatch.com/investing/stock/{}/financials/balance-sheet",
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},
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"cashflow": {
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"quarter": "https://www.marketwatch.com/investing/stock/{}/financials/cash-flow/quarter",
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"annual": "https://www.marketwatch.com/investing/stock/{}/financials/cash-flow",
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},
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}
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if statement not in financial_urls.keys():
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raise ValueError(f"type {statement} is not in {financial_urls.keys()}")
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if quarter:
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period = "quarter"
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else:
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period = "annual"
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text_soup_financials = BeautifulSoup(
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requests.get(
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financial_urls[statement][period].format(ticker),
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headers={"User-Agent": get_user_agent()},
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).text,
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"lxml",
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)
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# Define financials columns
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a_financials_header = list()
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for financials_header in text_soup_financials.findAll(
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"th", {"class": "overflow__heading"}
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):
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a_financials_header.append(financials_header.text.strip("\n").split("\n")[0])
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s_header_end_trend = ("5-year trend", "5- qtr trend")[quarter]
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df_financials = pd.DataFrame(
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columns=a_financials_header[0 : a_financials_header.index(s_header_end_trend)]
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)
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find_table = text_soup_financials.findAll(
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"div", {"class": "element element--table table--fixed financials"}
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)
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if not find_table:
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return df_financials
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financials_rows = find_table[0].findAll(
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"tr", {"class": ["table__row is-highlighted", "table__row"]}
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)
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for a_row in financials_rows:
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constructed_row = list()
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financial_columns = a_row.findAll(
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"td", {"class": ["overflow__cell", "overflow__cell fixed--column"]}
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)
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if not financial_columns:
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continue
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for a_column in financial_columns:
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column_to_text = a_column.text.strip()
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if "\n" in column_to_text:
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column_to_text = column_to_text.split("\n")[0]
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if column_to_text == "":
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continue
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constructed_row.append(column_to_text)
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df_financials.loc[len(df_financials)] = constructed_row
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return df_financials
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def prepare_comparison_financials(
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similar: List[str], statement: str, quarter: bool
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) -> Tuple[List[str], Dict[str, pd.DataFrame]]:
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"""Builds a dictionary of DataFrame with financial statements for list of tickers
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Parameters
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----------
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similar : List[str]
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List of similar stock tickers
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statement : str
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Either income, balance or cashflow
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quarter : bool
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Return quarterly financial statements instead of annual, by default False
|
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Returns
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-------
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List[str]
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List of index headers
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Dict[str, pd.DataFrame]
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A dictionary of DataFrame with financial info from list of similar tickers
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"""
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financials = {}
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# Get financial dataframe of each company
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for symbol in similar:
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financials[symbol] = prepare_df_financials(
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symbol, statement, quarter
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).set_index("Item")
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items = []
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# Get common headers between tickers
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for symbol in similar:
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if len(financials[symbol].columns) > len(items):
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items = financials[symbol].columns
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# Add columns with N/A when data is not available, to have similar columns
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for symbol in similar:
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if len(financials[symbol].columns) < len(items):
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for item in items:
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if item not in financials[symbol].columns:
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financials[symbol][item] = "N/A"
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financials[symbol] = financials[symbol].reindex(sorted(items), axis=1)
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return list(items), financials
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def combine_similar_financials(
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financials: Dict[str, pd.DataFrame],
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similar: List[str],
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timeframe: str,
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) -> pd.DataFrame:
|
||||
"""Builds a DataFrame with financial statements from a certain timeframe of a list of tickers
|
||||
|
||||
Parameters
|
||||
----------
|
||||
Dict[str, pd.DataFrame]
|
||||
A dictionary of DataFrame with financial info from list of similar tickers
|
||||
similar : List[str]
|
||||
List of similar stock tickers
|
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statement : str
|
||||
Either income, balance or cashflow
|
||||
|
||||
Returns
|
||||
-------
|
||||
pd.DataFrame
|
||||
A DataFrame with financial statements from a certain timeframe of a list of tickers
|
||||
"""
|
||||
|
||||
compare_financials = financials[similar[0]][timeframe].to_frame()
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compare_financials.rename(columns={timeframe: similar[0]}, inplace=True)
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|
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for symbol in similar[1:]:
|
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compare_financials[symbol] = financials[symbol][timeframe]
|
||||
|
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return compare_financials
|
||||
@@ -293,7 +293,9 @@ def parse_known_args_and_warn(parser, l_args):
|
||||
|
||||
|
||||
def financials_colored_values(val: str) -> str:
|
||||
if sum(c.isalpha() for c in val) < 2:
|
||||
if val == "N/A":
|
||||
val = f"{Fore.YELLOW}{val}{Style.RESET_ALL}"
|
||||
elif sum(c.isalpha() for c in val) < 2:
|
||||
if "%" in val:
|
||||
if "-" in val:
|
||||
val = f"{Fore.RED}{val}{Style.RESET_ALL}"
|
||||
|
||||
Reference in New Issue
Block a user