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[Bot] Combine APIs and create typings
1 parent 7c51e78 commit 9a83837

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+5352
-1078
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‎data/api.json

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‎data/typing/numpy.py

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@@ -352,6 +352,7 @@
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# usage.networkx: 2
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# usage.pandas: 1
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# usage.prophet: 3
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# usage.pyjanitor: 1
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# usage.scipy: 49
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# usage.seaborn: 2
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# usage.skimage: 31
@@ -874,6 +875,7 @@
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# usage.matplotlib: 38
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# usage.networkx: 1
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# usage.pandas: 77
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# usage.pyjanitor: 1
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# usage.scipy: 763
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# usage.seaborn: 9
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# usage.skimage: 36
@@ -965,6 +967,7 @@
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# usage.matplotlib: 6
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# usage.pandas: 31
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# usage.prophet: 2
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# usage.pyjanitor: 1
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# usage.scipy: 58
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# usage.skimage: 2
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# usage.sklearn: 12
@@ -1170,6 +1173,7 @@
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# usage.koalas: 10
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# usage.matplotlib: 1
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# usage.pandas: 16
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# usage.pyjanitor: 1
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# usage.scipy: 101
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# usage.skimage: 13
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# usage.sklearn: 2
@@ -1193,6 +1197,7 @@
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# usage.koalas: 10
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# usage.matplotlib: 3
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# usage.pandas: 14
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# usage.pyjanitor: 2
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# usage.scipy: 21
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# usage.skimage: 5
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# usage.sklearn: 14
@@ -1266,6 +1271,7 @@
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# usage.dask: 6
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# usage.matplotlib: 7
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# usage.pandas: 12
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# usage.pyjanitor: 2
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# usage.scipy: 21
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# usage.skimage: 30
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# usage.sklearn: 27
@@ -1294,6 +1300,7 @@
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# usage.matplotlib: 8
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# usage.networkx: 2
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# usage.pandas: 11
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# usage.pyjanitor: 2
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# usage.scipy: 16
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# usage.skimage: 6
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# usage.sklearn: 24
@@ -1444,6 +1451,7 @@
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# usage.dask: 6
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# usage.geopandas: 1
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# usage.pandas: 21
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# usage.pyjanitor: 1
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# usage.scipy: 3
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# usage.sklearn: 3
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# usage.statsmodels: 1
@@ -3316,6 +3324,7 @@ def amax(a: numpy.ndarray):
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"""
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usage.dask: 11
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usage.matplotlib: 35
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usage.pyjanitor: 1
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usage.scipy: 132
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usage.seaborn: 2
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usage.skimage: 81
@@ -4057,6 +4066,7 @@ def amax(
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usage.matplotlib: 70
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usage.pandas: 41
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usage.pyjanitor: 1
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usage.scipy: 188
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usage.seaborn: 4
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usage.skimage: 110
@@ -4072,6 +4082,7 @@ def amin(a: numpy.ndarray):
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"""
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usage.dask: 14
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usage.matplotlib: 31
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usage.pyjanitor: 1
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usage.scipy: 49
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usage.seaborn: 1
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usage.skimage: 54
@@ -4751,6 +4762,7 @@ def amin(
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usage.networkx: 2
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usage.pandas: 53
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usage.pyjanitor: 1
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usage.scipy: 98
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usage.seaborn: 2
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usage.skimage: 62
@@ -20861,6 +20873,14 @@ def array(
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...
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@overload
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def array(_0: unyt.array.unyt_array, /):
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"""
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usage.pyjanitor: 1
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"""
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...
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@overload
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def array(_0: List[Tuple[str, int]], /, *, dtype: Type[object]):
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"""
@@ -23270,6 +23290,7 @@ def array(
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usage.networkx: 137
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usage.pandas: 6865
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usage.prophet: 31
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usage.pyjanitor: 1
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usage.sample-usage: 3
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usage.scipy: 7182
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usage.seaborn: 126
@@ -56111,6 +56132,7 @@ def issubdtype(arg1: numpy.dtype, arg2: Type[numpy.complexfloating]):
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def issubdtype(arg1: numpy.dtype, arg2: Type[numpy.number]):
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"""
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usage.dask: 16
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usage.pyjanitor: 2
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usage.scipy: 8
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usage.xarray: 13
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"""
@@ -56487,6 +56509,7 @@ def issubdtype(
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usage.dask: 49
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usage.matplotlib: 35
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usage.pandas: 83
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usage.pyjanitor: 2
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usage.scipy: 466
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usage.skimage: 165
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usage.sklearn: 44
@@ -60055,6 +60078,7 @@ def mean(a: numpy.ndarray):
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usage.dask: 21
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usage.matplotlib: 7
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usage.prophet: 1
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usage.pyjanitor: 1
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usage.scipy: 26
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usage.seaborn: 3
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usage.skimage: 36
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usage.networkx: 6
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usage.pandas: 26
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usage.prophet: 2
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usage.pyjanitor: 1
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usage.scipy: 89
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usage.seaborn: 8
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usage.skimage: 62
@@ -60695,6 +60720,7 @@ def median(a: numpy.ndarray, axis: Tuple[int, int]):
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def median(a: numpy.ndarray):
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"""
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usage.matplotlib: 2
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usage.pyjanitor: 1
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usage.scipy: 18
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usage.seaborn: 2
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usage.skimage: 4
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usage.matplotlib: 3
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usage.pandas: 17
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usage.prophet: 9
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usage.pyjanitor: 1
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usage.scipy: 28
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usage.seaborn: 3
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usage.skimage: 5
@@ -81205,6 +81232,7 @@ def zeros(_0: int, /):
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usage.matplotlib: 38
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usage.networkx: 2
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usage.prophet: 6
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usage.pyjanitor: 1
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usage.scipy: 263
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usage.seaborn: 5
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usage.skimage: 15
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usage.networkx: 26
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usage.pandas: 125
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usage.prophet: 7
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usage.pyjanitor: 1
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usage.sample-usage: 1
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usage.scipy: 2108
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usage.seaborn: 12
@@ -100024,6 +100053,7 @@ def __rsub__(self, _0: numpy.int64, /):
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"""
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usage.dask: 1
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usage.matplotlib: 8
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usage.pyjanitor: 1
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usage.scipy: 46
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usage.seaborn: 1
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usage.skimage: 11
@@ -100137,12 +100167,20 @@ def __rsub__(self, _0: object, /):
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"""
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@overload
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def __rsub__(self, _0: pandas.core.series.Series, /):
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"""
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"""
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def __rsub__(self, _0: object, /):
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"""
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usage.dask: 4
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usage.matplotlib: 15
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usage.pandas: 32
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usage.prophet: 1
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usage.pyjanitor: 2
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usage.scipy: 94
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usage.seaborn: 1
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usage.skimage: 30
@@ -100257,6 +100295,13 @@ def __rtruediv__(self, _0: numpy.ma.core.MaskedArray, /):
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"""
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@overload
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def __rtruediv__(self, _0: pandas.core.series.Series, /):
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"""
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"""
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@overload
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def __rtruediv__(self, _0: decimal.Decimal, /):
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"""
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usage.networkx: 2
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usage.pandas: 5
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usage.prophet: 2
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usage.pyjanitor: 1
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usage.scipy: 49
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usage.seaborn: 4
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usage.skimage: 11
@@ -100340,6 +100386,7 @@ def __sub__(self, _0: numpy.int64, /):
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"""
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usage.dask: 1
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usage.matplotlib: 8
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usage.pyjanitor: 1
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usage.scipy: 46
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usage.seaborn: 1
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usage.skimage: 11
@@ -100399,6 +100446,7 @@ def __sub__(self, _0: object, /):
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usage.matplotlib: 33
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usage.pandas: 26
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usage.prophet: 3
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usage.pyjanitor: 1
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usage.scipy: 154
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usage.seaborn: 8
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usage.skimage: 25
@@ -108332,6 +108380,7 @@ def __getitem__(self, _0: int, /):
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usage.modin: 20
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usage.networkx: 52
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usage.prophet: 28
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usage.pyjanitor: 2
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usage.sample-usage: 2
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usage.scipy: 2217
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usage.seaborn: 74
@@ -116132,6 +116181,7 @@ def __getitem__(self, _0: object, /):
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usage.networkx: 215
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usage.pandas: 2206
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usage.prophet: 41
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usage.pyjanitor: 2
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usage.sample-usage: 5
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usage.scipy: 9090
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usage.seaborn: 245
@@ -117145,6 +117195,7 @@ def __iter__(self, /):
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usage.networkx: 11
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usage.pandas: 181
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usage.prophet: 1
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usage.pyjanitor: 1
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usage.sample-usage: 2
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usage.scipy: 302
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usage.seaborn: 102
@@ -118190,6 +118241,13 @@ def __mul__(self, _0: numpy.ma.core.MaskedArray, /):
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"""
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@overload
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def __mul__(self, _0: unyt.unit_object.Unit, /):
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"""
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usage.pyjanitor: 1
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"""
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def __mul__(self, _0: Tuple[int, int, int], /):
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usage.pandas: 256
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usage.prophet: 23
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usage.sample-usage: 1
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usage.scipy: 2349
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@@ -137470,6 +137529,7 @@ def __call__(self, _0: pandas.core.series.Series, _1: pandas.core.series.Series,
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usage.pyjanitor: 4
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usage.sample-usage: 3
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usage.scipy: 8018
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usage.seaborn: 43

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