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Add income,cashflow,balance comparison

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This commit is contained in:
didier
2021-03-20 00:59:30 +00:00
parent 4cf1590872
commit 9194d4af6f
3 changed files with 229 additions and 109 deletions
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14
gamestonk_terminal/comparison_analysis/ca_controller.py
View File

@@ -29,6 +29,8 @@ class ComparisonAnalysisController:
"historical",
"corr",
"income",
"balance",
"cash",
]
def __init__(
@@ -80,6 +82,8 @@ class ComparisonAnalysisController:
print(" corr correlation between similar companies")
print("")
print(" income income financials comparison")
print(" balance balance financials comparison")
print(" cash cash financials comparison")
print("")
return
@@ -126,7 +130,7 @@ class ComparisonAnalysisController:
"-s",
"--similar",
dest="l_similar",
type=lambda s: [str(item) for item in s.split(",")],
type=lambda s: [str(item).upper() for item in s.split(",")],
default=[],
help="similar companies to compare with.",
)
@@ -201,6 +205,14 @@ class ComparisonAnalysisController:
"""Process income command"""
mw_api.compare_income(other_args, self.ticker, self.similar)
def call_balance(self, other_args: List[str]):
"""Process balance command"""
mw_api.compare_balance(other_args, self.ticker, self.similar)
def call_cash(self, other_args: List[str]):
"""Process cash command"""
mw_api.compare_cashflow(other_args, self.ticker, self.similar)
def menu(stock: pd.DataFrame, ticker: str, start: datetime, interval: str):
"""Comparison Analysis Menu"""

319
gamestonk_terminal/comparison_analysis/market_watch_api.py
View File

@@ -39,15 +39,15 @@ def compare_income(other_args: List[str], ticker: str, similar: List[str]):
"-s",
"--similar",
dest="l_similar",
type=lambda s: [str(item) for item in s.split(",")],
default=[],
type=lambda s: [str(item).upper() for item in s.split(",")],
default=similar,
help="similar companies to compare with.",
)
parser.add_argument(
"-a",
"--also",
dest="l_also",
type=lambda s: [str(item) for item in s.split(",")],
type=lambda s: [str(item).upper() for item in s.split(",")],
default=[],
help="apart from loaded similar companies also compare with.",
)
@@ -73,29 +73,31 @@ def compare_income(other_args: List[str], ticker: str, similar: List[str]):
if not ns_parser:
return
if ns_parser.l_similar:
similar = ns_parser.l_similar
similar += ns_parser.l_also
l_similar = ns_parser.l_similar
l_similar += ns_parser.l_also
# Add main ticker to similar list of companies
similar.insert(0, ticker)
l_similar.insert(0, ticker)
l_timeframes, ddf_financials = prepare_comparison_financials(
similar, "income", ns_parser.b_quarter
l_similar, "income", ns_parser.b_quarter
)
if ns_parser.s_timeframe:
if ns_parser.s_timeframe not in l_timeframes:
raise ValueError(
f"Timeframe {ns_parser.s_timeframe} should be one of {l_timeframes}"
f"Timeframe selected should be one of {', '.join(l_timeframes)}"
)
s_timeframe = ns_parser.s_timeframe
else:
s_timeframe = l_timeframes[-1]
print(
f"Other available {('yearly', 'quarterly')[ns_parser.b_quarter]} timeframes are: {', '.join(l_timeframes)}\n"
)
df_financials_compared = combine_similar_financials(
ddf_financials, similar, s_timeframe
ddf_financials, l_similar, s_timeframe, ns_parser.b_quarter
)
if gtff.USE_COLOR:
@@ -107,147 +109,224 @@ def compare_income(other_args: List[str], ticker: str, similar: List[str]):
pd.set_option("display.max_colwidth", None)
pd.set_option("display.max_rows", None)
df_financials_compared.index.name = s_timeframe
if not ns_parser.b_quarter:
df_financials_compared.index.name = s_timeframe
print(df_financials_compared.to_string())
print("")
except Exception as e:
print(e)
print("")
print(e, "\n")
return
def balance(l_args, s_ticker):
def compare_balance(other_args: List[str], ticker: str, similar: List[str]):
"""Compare balance between companies
Parameters
----------
other_args : List[str]
Command line arguments to be processed with argparse
ticker : str
Main ticker to compare income
similar : List[str]
Similar companies to compare income with
"""
parser = argparse.ArgumentParser(
add_help=False,
prog="balance",
prog="compare_balance",
description="""
Prints either yearly or quarterly assets from balance sheet of the company.
The following fields are expected: Cash & Short Term Investments, Cash & Short Term
Investments Growth, Cash Only, Short-Term Investments, Cash & ST Investments / Total
Assets, Total Accounts Receivable, Total Accounts Receivable Growth, Accounts
Receivables, Net, Accounts Receivables, Gross, Bad Debt/Doubtful Accounts, Other
Receivable, Accounts Receivable Turnover, Inventories, Finished Goods, Work in
Progress, Raw Materials, Progress Payments & Other, Other Current Assets,
Miscellaneous Current Assets, Net Property, Plant & Equipment, Property, Plant &
Equipment - Gross, Buildings, Land & Improvements, Computer Software and Equipment,
Other Property, Plant & Equipment, Accumulated Depreciation, Total Investments and
Advances, Other Long-Term Investments, Long-Term Note Receivables, Intangible Assets,
Net Goodwill, Net Other Intangibles, Other Assets.
Prints either yearly or quarterly liabilities and shareholders' equity from balance
sheet of the company. The following fields are expected: ST Debt & Current Portion LT
Debt, Short Term Debt, Current Portion of Long Term Debt, Accounts Payable, Accounts
Payable Growth, Income Tax Payable, Other Current Liabilities, Dividends Payable,
Accrued Payroll, Miscellaneous Current Liabilities, Long-Term Debt, Long-Term Debt
excl. Capitalized Leases, Non-Convertible Debt, Convertible Debt, Capitalized Lease
Obligations, Provision for Risks & Charges, Deferred Taxes, Deferred Taxes - Credits,
Deferred Taxes - Debit, Other Liabilities, Other Liabilities (excl. Deferred Income),
Deferred Income, Non-Equity Reserves, Total Liabilities / Total Assets, Preferred Stock
(Carrying Value), Redeemable Preferred Stock, Non-Redeemable Preferred Stock, Common
Equity (Total), Common Equity/Total Assets, Common Stock Par/Carry Value, Retained
Earnings, ESOP Debt Guarantee, Cumulative Translation Adjustment/Unrealized For. Exch.
Gain, Unrealized Gain/Loss Marketable Securities, Revaluation Reserves, Treasury Stock,
Total Shareholders' Equity, Total Shareholders' Equity / Total Assets, Accumulated
Minority Interest, Total Equity, Total Current Assets, Total Assets, Total Current
Liabilities, Total Liabilities, and Liabilities & Shareholders' Equity.
[Source: Market Watch]
Prints either yearly or quarterly balance statement the company, and compares
it against similar companies. [Source: Market Watch]
""",
)
parser.add_argument(
"-s",
"--similar",
dest="l_similar",
type=lambda s: [str(item).upper() for item in s.split(",")],
default=similar,
help="similar companies to compare with.",
)
parser.add_argument(
"-a",
"--also",
dest="l_also",
type=lambda s: [str(item).upper() for item in s.split(",")],
default=[],
help="apart from loaded similar companies also compare with.",
)
parser.add_argument(
"-q",
"--quarter",
action="store_true",
default=False,
dest="b_quarter",
help="Quarter fundamental data flag.",
help="Quarter financial data flag.",
)
parser.add_argument(
"-t",
"--timeframe",
dest="s_timeframe",
type=str,
default=None,
help="Specify yearly/quarterly timeframe. Default is last.",
)
try:
ns_parser = parse_known_args_and_warn(parser, l_args)
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
df_financials = prepare_df_financials(s_ticker, "balance", ns_parser.b_quarter)
l_similar = ns_parser.l_similar
l_similar += ns_parser.l_also
# Add main ticker to similar list of companies
l_similar.insert(0, ticker)
l_timeframes, ddf_financials = prepare_comparison_financials(
l_similar, "balance", ns_parser.b_quarter
)
if ns_parser.s_timeframe:
if ns_parser.s_timeframe not in l_timeframes:
raise ValueError(
f"Timeframe selected should be one of {', '.join(l_timeframes)}"
)
s_timeframe = ns_parser.s_timeframe
else:
s_timeframe = l_timeframes[-1]
print(
f"Other available {('yearly', 'quarterly')[ns_parser.b_quarter]} timeframes are: {', '.join(l_timeframes)}\n"
)
df_financials_compared = combine_similar_financials(
ddf_financials, l_similar, s_timeframe, ns_parser.b_quarter
)
if gtff.USE_COLOR:
df_financials = df_financials.applymap(financials_colored_values)
df_financials_compared = df_financials_compared.applymap(
financials_colored_values
)
patch_pandas_text_adjustment()
pd.set_option("display.max_colwidth", None)
pd.set_option("display.max_rows", None)
print(df_financials.to_string(index=False))
if not ns_parser.b_quarter:
df_financials_compared.index.name = s_timeframe
print(df_financials_compared.to_string())
print("")
except Exception as e:
print(e)
print("")
print(e, "\n")
return
def cash(l_args, s_ticker):
def compare_cashflow(other_args: List[str], ticker: str, similar: List[str]):
"""Compare balance between companies
Parameters
----------
other_args : List[str]
Command line arguments to be processed with argparse
ticker : str
Main ticker to compare income
similar : List[str]
Similar companies to compare income with
"""
parser = argparse.ArgumentParser(
add_help=False,
prog="cash_flow",
prog="compare_cashflow",
description="""
Prints either yearly or quarterly cash flow operating activities of the company.
The following fields are expected: Net Income before Extraordinaries, Net Income
Growth, Depreciation, Depletion & Amortization, Depreciation and Depletion,
Amortization of Intangible Assets, Deferred Taxes & Investment Tax Credit, Deferred
Taxes, Investment Tax Credit, Other Funds, Funds from Operations, Extraordinaries,
Changes in Working Capital, Receivables, Accounts Payable, Other Assets/Liabilities,
and Net Operating Cash Flow Growth.
Prints either yearly or quarterly cash flow investing activities of the company.
The following fields are expected: Capital Expenditures, Capital Expenditures Growth,
Capital Expenditures/Sales, Capital Expenditures (Fixed Assets), Capital Expenditures
(Other Assets), Net Assets from Acquisitions, Sale of Fixed Assets & Businesses,
Purchase/Sale of Investments, Purchase of Investments, Sale/Maturity of Investments,
Other Uses, Other Sources, Net Investing Cash Flow Growth.
Prints either yearly or quarterly cash flow financing activities of the company.
The following fields are expected: Cash Dividends Paid - Total, Common Dividends,
Preferred Dividends, Change in Capital Stock, Repurchase of Common & Preferred Stk.,
Sale of Common & Preferred Stock, Proceeds from Stock Options, Other Proceeds from Sale
of Stock, Issuance/Reduction of Debt, Net, Change in Current Debt, Change in Long-Term
Debt, Issuance of Long-Term Debt, Reduction in Long-Term Debt, Other Funds, Other Uses,
Other Sources, Net Financing Cash Flow Growth, Net Financing Cash Flow/Sales, Exchange
Rate Effect, Miscellaneous Funds, Net Change in Cash, Free Cash Flow, Free Cash Flow
Growth, Free Cash Flow Yield, Net Operating Cash Flow, Net Investing Cash Flow, Net
Financing Cash Flow.
[Source: Market Watch]
Prints either yearly or quarterly cash statement the company, and compares
it against similar companies. [Source: Market Watch]
""",
)
parser.add_argument(
"-s",
"--similar",
dest="l_similar",
type=lambda s: [str(item).upper() for item in s.split(",")],
default=similar,
help="similar companies to compare with.",
)
parser.add_argument(
"-a",
"--also",
dest="l_also",
type=lambda s: [str(item).upper() for item in s.split(",")],
default=[],
help="apart from loaded similar companies also compare with.",
)
parser.add_argument(
"-q",
"--quarter",
action="store_true",
default=False,
dest="b_quarter",
help="Quarter fundamental data flag.",
help="Quarter financial data flag.",
)
parser.add_argument(
"-t",
"--timeframe",
dest="s_timeframe",
type=str,
default=None,
help="Specify yearly/quarterly timeframe. Default is last.",
)
try:
ns_parser = parse_known_args_and_warn(parser, l_args)
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
df_financials = prepare_df_financials(s_ticker, "cashflow", ns_parser.b_quarter)
l_similar = ns_parser.l_similar
l_similar += ns_parser.l_also
# Add main ticker to similar list of companies
l_similar.insert(0, ticker)
l_timeframes, ddf_financials = prepare_comparison_financials(
l_similar, "cashflow", ns_parser.b_quarter
)
if ns_parser.s_timeframe:
if ns_parser.s_timeframe not in l_timeframes:
raise ValueError(
f"Timeframe selected should be one of {', '.join(l_timeframes)}"
)
s_timeframe = ns_parser.s_timeframe
else:
s_timeframe = l_timeframes[-1]
print(
f"Other available {('yearly', 'quarterly')[ns_parser.b_quarter]} timeframes are: {', '.join(l_timeframes)}\n"
)
df_financials_compared = combine_similar_financials(
ddf_financials, l_similar, s_timeframe, ns_parser.b_quarter
)
if gtff.USE_COLOR:
df_financials = df_financials.applymap(financials_colored_values)
df_financials_compared = df_financials_compared.applymap(
financials_colored_values
)
patch_pandas_text_adjustment()
pd.set_option("display.max_colwidth", None)
pd.set_option("display.max_rows", None)
print(df_financials.to_string(index=False))
if not ns_parser.b_quarter:
df_financials_compared.index.name = s_timeframe
print(df_financials_compared.to_string())
print("")
except Exception as e:
print(e)
print("")
print(e, "\n")
return
@@ -381,19 +460,23 @@ def prepare_comparison_financials(
symbol, statement, quarter
).set_index("Item")
items = []
# Get common headers between tickers
for symbol in similar:
if len(financials[symbol].columns) > len(items):
items = financials[symbol].columns
if quarter:
items = financials[similar[0]].columns
# Add columns with N/A when data is not available, to have similar columns
for symbol in similar:
if len(financials[symbol].columns) < len(items):
for item in items:
if item not in financials[symbol].columns:
financials[symbol][item] = "N/A"
financials[symbol] = financials[symbol].reindex(sorted(items), axis=1)
else:
items = []
# Get common headers between tickers
for symbol in similar:
if len(financials[symbol].columns) > len(items):
items = financials[symbol].columns
# Add columns with N/A when data is not available, to have similar columns
for symbol in similar:
if len(financials[symbol].columns) < len(items):
for item in items:
if item not in financials[symbol].columns:
financials[symbol][item] = "N/A"
financials[symbol] = financials[symbol].reindex(sorted(items), axis=1)
return list(items), financials
@@ -402,28 +485,52 @@ def combine_similar_financials(
financials: Dict[str, pd.DataFrame],
similar: List[str],
timeframe: str,
quarter: bool,
) -> pd.DataFrame:
"""Builds a DataFrame with financial statements from a certain timeframe of a list of tickers
Parameters
----------
Dict[str, pd.DataFrame]
financials : Dict[str, pd.DataFrame]
A dictionary of DataFrame with financial info from list of similar tickers
similar : List[str]
List of similar stock tickers
statement : str
Either income, balance or cashflow
quarter : bool
False for yearly data, True for quarterly
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()
compare_financials.rename(columns={timeframe: similar[0]}, inplace=True)
# Quarter data is a bit more confusing for comparison due to the fact that
# the reports may occur at slight different moments. Hence we rely on the
# order set by the Market Watch website
for symbol in similar[1:]:
compare_financials[symbol] = financials[symbol][timeframe]
if quarter:
compare_financials = financials[similar[0]][timeframe].to_frame()
compare_financials.rename(columns={timeframe: similar[0]}, inplace=True)
earnings_dates = [timeframe]
idx = len(financials[similar[0]].columns) - list(
financials[similar[0]].columns
).index(timeframe)
for symbol in similar[1:]:
report_quarter_date = list(financials[symbol].columns)[-idx]
earnings_dates.append(report_quarter_date)
compare_financials[symbol] = financials[symbol][report_quarter_date]
compare_financials.columns = pd.MultiIndex.from_tuples(
zip(earnings_dates, compare_financials.columns),
)
else:
compare_financials = financials[similar[0]][timeframe].to_frame()
compare_financials.rename(columns={timeframe: similar[0]}, inplace=True)
for symbol in similar[1:]:
compare_financials[symbol] = financials[symbol][timeframe]
return compare_financials

5
gamestonk_terminal/helper_funcs.py
View File

@@ -293,8 +293,8 @@ def parse_known_args_and_warn(parser, l_args):
def financials_colored_values(val: str) -> str:
if val == "N/A":
val = f"{Fore.YELLOW}{val}{Style.RESET_ALL}"
if val == "N/A" or str(val) == "nan":
val = f"{Fore.YELLOW}N/A{Style.RESET_ALL}"
elif sum(c.isalpha() for c in val) < 2:
if "%" in val:
if "-" in val:
@@ -303,6 +303,7 @@ def financials_colored_values(val: str) -> str:
val = f"{Fore.GREEN}{val}{Style.RESET_ALL}"
elif "(" in val:
val = f"{Fore.RED}{val}{Style.RESET_ALL}"
return val