diff --git a/yfinance/base.py b/yfinance/base.py index 894d23047..90c2813c4 100644 --- a/yfinance/base.py +++ b/yfinance/base.py @@ -739,7 +739,7 @@ def _get_earnings_dates_using_scrape(self, limit = 12, offset = 0) -> Optional[p df = df.drop(["Symbol", "Company"], axis=1) # Backwards compatibility - df.rename(columns={'Surprise (%)': 'Surprise(%)'}, inplace=True) + df = df.rename(columns={'Surprise (%)': 'Surprise(%)'}) df = df.dropna(subset="Earnings Date") @@ -825,9 +825,9 @@ def _get_earnings_dates_using_screener(self, limit=12) -> Optional[pd.DataFrame] df[columns_to_update] = df[columns_to_update].astype('float64').replace(0.0, np.nan) # Format the dataframe - df.drop(['Event Start Date', 'Timezone short name'], axis=1, inplace=True) - df.set_index('Earnings Date', inplace=True) - df.rename(columns={'Surprise (%)': 'Surprise(%)'}, inplace=True) # Compatibility + df = df.drop(['Event Start Date', 'Timezone short name'], axis=1) + df = df.set_index('Earnings Date') + df = df.rename(columns={'Surprise (%)': 'Surprise(%)'}) # Compatibility self._earnings_dates[limit] = df return df diff --git a/yfinance/calendars.py b/yfinance/calendars.py index 93f05dfbc..adb23deea 100644 --- a/yfinance/calendars.py +++ b/yfinance/calendars.py @@ -282,9 +282,9 @@ def _cleanup_df(self, calendar_type: str, df: pd.DataFrame) -> pd.DataFrame: df[nan_cols] = df[nan_cols].astype("float64").replace(0.0, np.nan) # Format the dataframe - df.set_index(predef_cal["df_index"], inplace=True) + df = df.set_index(predef_cal["df_index"]) for rename_from, rename_to in predef_cal["renames"].items(): - df.rename(columns={rename_from: rename_to}, inplace=True) + df = df.rename(columns={rename_from: rename_to}) for datetime_col in predef_cal["datetime_cols"]: df[datetime_col] = pd.to_datetime(df[datetime_col]) diff --git a/yfinance/multi.py b/yfinance/multi.py index 222a31ab8..d5395440e 100644 --- a/yfinance/multi.py +++ b/yfinance/multi.py @@ -218,11 +218,11 @@ def _download_impl(ctx, tickers, start=None, end=None, actions=False, threads=Tr except Exception: data = _pd.concat(ctx.dfs.values(), axis=1, sort=True, keys=ctx.dfs.keys(), names=['Ticker', 'Price']) - data.rename(columns=ctx.isins, inplace=True) + data = data.rename(columns=ctx.isins) if group_by == 'column' and isinstance(data.columns, _pd.MultiIndex): data.columns = data.columns.swaplevel(0, 1) - data.sort_index(level=0, axis=1, inplace=True) + data = data.sort_index(level=0, axis=1) if not multi_level_index and len(tickers) == 1: data = data.droplevel(0 if group_by == 'ticker' else 1, axis=1).rename_axis(None, axis=1) diff --git a/yfinance/scrapers/analysis.py b/yfinance/scrapers/analysis.py index 432f28206..e7dead6fb 100644 --- a/yfinance/scrapers/analysis.py +++ b/yfinance/scrapers/analysis.py @@ -173,7 +173,7 @@ def _fetch_earnings_history(self, methodology) -> pd.DataFrame: df = pd.DataFrame(rows) if 'quarter' in df.columns: df['quarter'] = pd.to_datetime(df['quarter'], format='%Y-%m-%d') - df.set_index('quarter', inplace=True) + df = df.set_index('quarter') label = _eps_methodology_label(methodology, module_data) if label is not None: diff --git a/yfinance/scrapers/holders.py b/yfinance/scrapers/holders.py index d2b030a2c..fcb0cac4f 100644 --- a/yfinance/scrapers/holders.py +++ b/yfinance/scrapers/holders.py @@ -116,7 +116,7 @@ def _parse_institution_ownership(self, data): df = pd.DataFrame(holders) if not df.empty: df["reportDate"] = pd.to_datetime(df["reportDate"], unit="s") - df.rename(columns={"reportDate": "Date Reported", "organization": "Holder", "position": "Shares", "value": "Value"}, inplace=True) # "pctHeld": "% Out" + df = df.rename(columns={"reportDate": "Date Reported", "organization": "Holder", "position": "Shares", "value": "Value"}) # "pctHeld": "% Out" self._institutional = df def _parse_fund_ownership(self, data): @@ -128,7 +128,7 @@ def _parse_fund_ownership(self, data): df = pd.DataFrame(holders) if not df.empty: df["reportDate"] = pd.to_datetime(df["reportDate"], unit="s") - df.rename(columns={"reportDate": "Date Reported", "organization": "Holder", "position": "Shares", "value": "Value"}, inplace=True) + df = df.rename(columns={"reportDate": "Date Reported", "organization": "Holder", "position": "Shares", "value": "Value"}) self._mutualfund = df def _parse_major_direct_holders(self, data): @@ -140,7 +140,7 @@ def _parse_major_direct_holders(self, data): df = pd.DataFrame(holders) if not df.empty: df["reportDate"] = pd.to_datetime(df["reportDate"], unit="s") - df.rename(columns={"reportDate": "Date Reported", "organization": "Holder", "positionDirect": "Shares", "valueDirect": "Value"}, inplace=True) + df = df.rename(columns={"reportDate": "Date Reported", "organization": "Holder", "positionDirect": "Shares", "valueDirect": "Value"}) self._major_direct_holders = df def _parse_major_holders_breakdown(self, data): @@ -149,7 +149,7 @@ def _parse_major_holders_breakdown(self, data): df = pd.DataFrame.from_dict(data, orient="index") if not df.empty: df.columns.name = "Breakdown" - df.rename(columns={df.columns[0]: 'Value'}, inplace=True) + df = df.rename(columns={df.columns[0]: 'Value'}) self._major = df def _parse_insider_transactions(self, data): @@ -161,7 +161,7 @@ def _parse_insider_transactions(self, data): df = pd.DataFrame(holders) if not df.empty: df["startDate"] = pd.to_datetime(df["startDate"], unit="s") - df.rename(columns={ + df = df.rename(columns={ "startDate": "Start Date", "filerName": "Insider", "filerRelation": "Position", @@ -171,7 +171,7 @@ def _parse_insider_transactions(self, data): "shares": "Shares", "value": "Value", "ownership": "Ownership" # ownership flag, direct or institutional - }, inplace=True) + }) self._insider_transactions = df def _parse_insider_holders(self, data): @@ -187,7 +187,7 @@ def _parse_insider_holders(self, data): if "latestTransDate" in df: df["latestTransDate"] = pd.to_datetime(df["latestTransDate"], unit="s") - df.rename(columns={ + df = df.rename(columns={ "name": "Name", "relation": "Position", "url": "URL", @@ -197,7 +197,7 @@ def _parse_insider_holders(self, data): "positionDirect": "Shares Owned Directly", "positionIndirectDate": "Position Indirect Date", "positionIndirect": "Shares Owned Indirectly" - }, inplace=True) + }) df["Name"] = df["Name"].astype(str) df["Position"] = df["Position"].astype(str) diff --git a/yfinance/scrapers/quote.py b/yfinance/scrapers/quote.py index 117c58c81..538a18979 100644 --- a/yfinance/scrapers/quote.py +++ b/yfinance/scrapers/quote.py @@ -572,8 +572,8 @@ def upgrades_downgrades(self) -> pd.DataFrame: if len(data) == 0: raise YFDataException(f"No upgrade/downgrade history found for {self._symbol}") df = pd.DataFrame(data) - df.rename(columns={"epochGradeDate": "GradeDate", 'firm': 'Firm', 'toGrade': 'ToGrade', 'fromGrade': 'FromGrade', 'action': 'Action'}, inplace=True) - df.set_index('GradeDate', inplace=True) + df = df.rename(columns={"epochGradeDate": "GradeDate", 'firm': 'Firm', 'toGrade': 'ToGrade', 'fromGrade': 'FromGrade', 'action': 'Action'}) + df = df.set_index('GradeDate') df.index = pd.to_datetime(df.index, unit='s') self._upgrades_downgrades = df except (KeyError, IndexError): diff --git a/yfinance/tickers.py b/yfinance/tickers.py index 6f5a54e92..77d41b22b 100644 --- a/yfinance/tickers.py +++ b/yfinance/tickers.py @@ -85,7 +85,7 @@ def download(self, period='1mo if start & end None', interval="1d", if group_by == 'column': data.columns = data.columns.swaplevel(0, 1) - data.sort_index(level=0, axis=1, inplace=True) + data = data.sort_index(level=0, axis=1) return data diff --git a/yfinance/utils.py b/yfinance/utils.py index 4e8f05e2e..e2c855dc1 100644 --- a/yfinance/utils.py +++ b/yfinance/utils.py @@ -511,14 +511,14 @@ def auto_adjust(data): df["Adj High"] = df["High"] * ratio df["Adj Low"] = df["Low"] * ratio - df.drop( + df = df.drop( ["Open", "High", "Low", "Close"], - axis=1, inplace=True) + axis=1) - df.rename(columns={ + df = df.rename(columns={ "Adj Open": "Open", "Adj High": "High", "Adj Low": "Low", "Adj Close": "Close" - }, inplace=True) + }) return df[[c for c in col_order if c in df.columns]] @@ -533,14 +533,14 @@ def back_adjust(data): df["Adj High"] = df["High"] * ratio df["Adj Low"] = df["Low"] * ratio - df.drop( + df = df.drop( ["Open", "High", "Low", "Adj Close"], - axis=1, inplace=True) + axis=1) - df.rename(columns={ + df = df.rename(columns={ "Adj Open": "Open", "Adj High": "High", "Adj Low": "Low" - }, inplace=True) + }) return df[[c for c in col_order if c in df.columns]] @@ -565,7 +565,7 @@ def parse_quotes(data): "Adj Close": adjclose, "Volume": volumes}) quotes.index = _pd.to_datetime(timestamps, unit="s") - quotes.sort_index(inplace=True) + quotes = quotes.sort_index() for c in ['Open', 'High', 'Low', 'Close', 'Adj Close']: if not is_float_dtype(quotes[c].dtype): # Only seen when Adj Close contains Infinity. @@ -582,9 +582,9 @@ def parse_actions(data): if "dividends" in data["events"] and len(data["events"]['dividends']) > 0: dividends = _pd.DataFrame( data=list(data["events"]["dividends"].values())) - dividends.set_index("date", inplace=True) + dividends = dividends.set_index("date") dividends.index = _pd.to_datetime(dividends.index, unit="s") - dividends.sort_index(inplace=True) + dividends = dividends.sort_index() if 'currency' in dividends.columns and (dividends['currency'] == '').all(): # Currency column useless, drop it. dividends = dividends.drop('currency', axis=1) @@ -593,17 +593,17 @@ def parse_actions(data): if "capitalGains" in data["events"] and len(data["events"]['capitalGains']) > 0: capital_gains = _pd.DataFrame( data=list(data["events"]["capitalGains"].values())) - capital_gains.set_index("date", inplace=True) + capital_gains = capital_gains.set_index("date") capital_gains.index = _pd.to_datetime(capital_gains.index, unit="s") - capital_gains.sort_index(inplace=True) + capital_gains = capital_gains.sort_index() capital_gains.columns = ["Capital Gains"] if "splits" in data["events"] and len(data["events"]['splits']) > 0: splits = _pd.DataFrame( data=list(data["events"]["splits"].values())) - splits.set_index("date", inplace=True) + splits = splits.set_index("date") splits.index = _pd.to_datetime(splits.index, unit="s") - splits.sort_index(inplace=True) + splits = splits.sort_index() splits["Stock Splits"] = splits["numerator"] / splits["denominator"] splits = splits[["Stock Splits"]]