TYP: pandas/core/frame.py (easy: bool/str)

pandas/core/frame.py

@@ -1440,7 +1440,7 @@ def to_numpy(
 
         return result
 
-    def to_dict(self, orient="dict", into=dict):
+    def to_dict(self, orient: str = "dict", into=dict):
         """
         Convert the DataFrame to a dictionary.
 
@@ -1615,15 +1615,15 @@ def to_dict(self, orient="dict", into=dict):
 
     def to_gbq(
         self,
-        destination_table,
-        project_id=None,
+        destination_table: str,
+        project_id: Optional[str] = None,
         chunksize=None,
-        reauth=False,
-        if_exists="fail",
-        auth_local_webserver=False,
+        reauth: bool = False,
+        if_exists: str = "fail",
+        auth_local_webserver: bool = False,
         table_schema=None,
-        location=None,
-        progress_bar=True,
+        location: Optional[str] = None,
+        progress_bar: bool = True,
         credentials=None,
     ) -> None:
         """
@@ -1728,7 +1728,7 @@ def from_records(
         index=None,
         exclude=None,
         columns=None,
-        coerce_float=False,
+        coerce_float: bool = False,
         nrows=None,
     ) -> DataFrame:
         """
@@ -2489,7 +2489,7 @@ def to_html(
         max_rows=None,
         max_cols=None,
         show_dimensions=False,
-        decimal=".",
+        decimal: str = ".",
         bold_rows=True,
         classes=None,
         escape=True,
@@ -3311,7 +3311,7 @@ def _box_col_values(self, values, loc: int) -> Series:
     # ----------------------------------------------------------------------
     # Unsorted
 
-    def query(self, expr, inplace=False, **kwargs):
+    def query(self, expr: str, inplace: bool = False, **kwargs):
         """
         Query the columns of a DataFrame with a boolean expression.
 
@@ -3475,7 +3475,7 @@ def query(self, expr, inplace=False, **kwargs):
         else:
             return result
 
-    def eval(self, expr, inplace=False, **kwargs):
+    def eval(self, expr: str, inplace: bool = False, **kwargs):
         """
         Evaluate a string describing operations on DataFrame columns.
 
@@ -3732,7 +3732,7 @@ def extract_unique_dtypes_from_dtypes_set(
 
         return self.iloc[:, keep_these.values]
 
-    def insert(self, loc, column, value, allow_duplicates=False) -> None:
+    def insert(self, loc, column, value, allow_duplicates: bool = False) -> None:
         """
         Insert column into DataFrame at specified location.
 
@@ -3846,7 +3846,7 @@ def assign(self, **kwargs) -> DataFrame:
             data[k] = com.apply_if_callable(v, data)
         return data
 
-    def _sanitize_column(self, key, value, broadcast=True):
+    def _sanitize_column(self, key, value, broadcast: bool = True):
         """
         Ensures new columns (which go into the BlockManager as new blocks) are
         always copied and converted into an array.
@@ -4046,7 +4046,7 @@ def _reindex_index(
         self,
         new_index,
         method,
-        copy,
+        copy: bool,
         level,
         fill_value=np.nan,
         limit=None,
@@ -4066,7 +4066,7 @@ def _reindex_columns(
         self,
         new_columns,
         method,
-        copy,
+        copy: bool,
         level,
         fill_value=None,
         limit=None,
@@ -4082,7 +4082,7 @@ def _reindex_columns(
             allow_dups=False,
         )
 
-    def _reindex_multi(self, axes, copy, fill_value) -> DataFrame:
+    def _reindex_multi(self, axes, copy: bool, fill_value) -> DataFrame:
         """
         We are guaranteed non-Nones in the axes.
         """
@@ -4106,12 +4106,12 @@ def _reindex_multi(self, axes, copy, fill_value) -> DataFrame:
     def align(
         self,
         other,
-        join="outer",
+        join: str = "outer",
         axis=None,
         level=None,
-        copy=True,
+        copy: bool = True,
         fill_value=None,
-        method=None,
+        method: Optional[str] = None,
         limit=None,
         fill_axis=0,
         broadcast_axis=None,
@@ -4199,8 +4199,8 @@ def drop(
         index=None,
         columns=None,
         level=None,
-        inplace=False,
-        errors="raise",
+        inplace: bool = False,
+        errors: str = "raise",
     ):
         """
         Drop specified labels from rows or columns.
@@ -4470,9 +4470,9 @@ def rename(
     def fillna(
         self,
         value=None,
-        method=None,
+        method: Optional[str] = None,
         axis=None,
-        inplace=False,
+        inplace: bool = False,
         limit=None,
         downcast=None,
     ) -> Optional[DataFrame]:
@@ -4533,10 +4533,10 @@ def replace(
         self,
         to_replace=None,
         value=None,
-        inplace=False,
+        inplace: bool = False,
         limit=None,
-        regex=False,
-        method="pad",
+        regex: bool = False,
+        method: str = "pad",
     ):
         return super().replace(
             to_replace=to_replace,
@@ -4616,7 +4616,12 @@ def shift(
         )
 
     def set_index(
-        self, keys, drop=True, append=False, inplace=False, verify_integrity=False
+        self,
+        keys,
+        drop: bool = True,
+        append: bool = False,
+        inplace: bool = False,
+        verify_integrity: bool = False,
     ):
         """
         Set the DataFrame index using existing columns.
@@ -5055,7 +5060,9 @@ def notna(self) -> DataFrame:
     def notnull(self) -> DataFrame:
         return ~self.isna()
 
-    def dropna(self, axis=0, how="any", thresh=None, subset=None, inplace=False):
+    def dropna(
+        self, axis=0, how: str = "any", thresh=None, subset=None, inplace: bool = False
+    ):
         """
         Remove missing values.
 
@@ -5436,10 +5443,10 @@ def sort_values(  # type: ignore[override]
         by,
         axis=0,
         ascending=True,
-        inplace=False,
-        kind="quicksort",
-        na_position="last",
-        ignore_index=False,
+        inplace: bool = False,
+        kind: str = "quicksort",
+        na_position: str = "last",
+        ignore_index: bool = False,
         key: ValueKeyFunc = None,
     ):
         inplace = validate_bool_kwarg(inplace, "inplace")
@@ -5701,7 +5708,7 @@ def value_counts(
 
         return counts
 
-    def nlargest(self, n, columns, keep="first") -> DataFrame:
+    def nlargest(self, n, columns, keep: str = "first") -> DataFrame:
         """
         Return the first `n` rows ordered by `columns` in descending order.
 
@@ -5810,7 +5817,7 @@ def nlargest(self, n, columns, keep="first") -> DataFrame:
         """
         return algorithms.SelectNFrame(self, n=n, keep=keep, columns=columns).nlargest()
 
-    def nsmallest(self, n, columns, keep="first") -> DataFrame:
+    def nsmallest(self, n, columns, keep: str = "first") -> DataFrame:
         """
         Return the first `n` rows ordered by `columns` in ascending order.
 
@@ -6234,7 +6241,7 @@ def compare(
         )
 
     def combine(
-        self, other: DataFrame, func, fill_value=None, overwrite=True
+        self, other: DataFrame, func, fill_value=None, overwrite: bool = True
     ) -> DataFrame:
         """
         Perform column-wise combine with another DataFrame.
@@ -6462,7 +6469,12 @@ def combiner(x, y):
         return self.combine(other, combiner, overwrite=False)
 
     def update(
-        self, other, join="left", overwrite=True, filter_func=None, errors="ignore"
+        self,
+        other,
+        join: str = "left",
+        overwrite: bool = True,
+        filter_func=None,
+        errors: str = "ignore",
     ) -> None:
         """
         Modify in place using non-NA values from another DataFrame.
@@ -7055,7 +7067,7 @@ def pivot_table(
             observed=observed,
         )
 
-    def stack(self, level=-1, dropna=True):
+    def stack(self, level=-1, dropna: bool = True):
         """
         Stack the prescribed level(s) from columns to index.
 
@@ -7636,7 +7648,7 @@ def transform(
         assert isinstance(result, DataFrame)
         return result
 
-    def apply(self, func, axis=0, raw=False, result_type=None, args=(), **kwds):
+    def apply(self, func, axis=0, raw: bool = False, result_type=None, args=(), **kwds):
         """
         Apply a function along an axis of the DataFrame.
 
@@ -7861,7 +7873,11 @@ def infer(x):
     # Merging / joining methods
 
     def append(
-        self, other, ignore_index=False, verify_integrity=False, sort=False
+        self,
+        other,
+        ignore_index: bool = False,
+        verify_integrity: bool = False,
+        sort: bool = False,
     ) -> DataFrame:
         """
         Append rows of `other` to the end of caller, returning a new object.
@@ -8002,7 +8018,13 @@ def append(
         ).__finalize__(self, method="append")
 
     def join(
-        self, other, on=None, how="left", lsuffix="", rsuffix="", sort=False
+        self,
+        other,
+        on=None,
+        how: str = "left",
+        lsuffix: str = "",
+        rsuffix: str = "",
+        sort: bool = False,
     ) -> DataFrame:
         """
         Join columns of another DataFrame.
@@ -8639,7 +8661,7 @@ def c(x):
     # ----------------------------------------------------------------------
     # ndarray-like stats methods
 
-    def count(self, axis=0, level=None, numeric_only=False):
+    def count(self, axis=0, level=None, numeric_only: bool = False):
         """
         Count non-NA cells for each column or row.
 
@@ -8794,8 +8816,8 @@ def _reduce(
         name: str,
         *,
         axis=0,
-        skipna=True,
-        numeric_only=None,
+        skipna: bool = True,
+        numeric_only: Optional[bool] = None,
         filter_type=None,
         **kwds,
     ):
@@ -8901,7 +8923,7 @@ def _get_data() -> DataFrame:
         result = self._constructor_sliced(result, index=labels)
         return result
 
-    def nunique(self, axis=0, dropna=True) -> Series:
+    def nunique(self, axis=0, dropna: bool = True) -> Series:
         """
         Count distinct observations over requested axis.
 
@@ -8941,7 +8963,7 @@ def nunique(self, axis=0, dropna=True) -> Series:
         """
         return self.apply(Series.nunique, axis=axis, dropna=dropna)
 
-    def idxmin(self, axis=0, skipna=True) -> Series:
+    def idxmin(self, axis=0, skipna: bool = True) -> Series:
         """
         Return index of first occurrence of minimum over requested axis.
 
@@ -9018,7 +9040,7 @@ def idxmin(self, axis=0, skipna=True) -> Series:
         result = [index[i] if i >= 0 else np.nan for i in indices]
         return self._constructor_sliced(result, index=self._get_agg_axis(axis))
 
-    def idxmax(self, axis=0, skipna=True) -> Series:
+    def idxmax(self, axis=0, skipna: bool = True) -> Series:
         """
         Return index of first occurrence of maximum over requested axis.
 
@@ -9106,7 +9128,9 @@ def _get_agg_axis(self, axis_num: int) -> Index:
         else:
             raise ValueError(f"Axis must be 0 or 1 (got {repr(axis_num)})")
 
-    def mode(self, axis=0, numeric_only=False, dropna=True) -> DataFrame:
+    def mode(
+        self, axis=0, numeric_only: bool = False, dropna: bool = True
+    ) -> DataFrame:
         """
         Get the mode(s) of each element along the selected axis.
 
@@ -9193,7 +9217,9 @@ def f(s):
 
         return data.apply(f, axis=axis)
 
-    def quantile(self, q=0.5, axis=0, numeric_only=True, interpolation="linear"):
+    def quantile(
+        self, q=0.5, axis=0, numeric_only: bool = True, interpolation: str = "linear"
+    ):
         """
         Return values at the given quantile over requested axis.