Merge pull request #556 from 1e-to/ser_doc3

Docs limitation and params fix + 5 func

Author: 1e-to

examples/series/series_append.py

@@ -0,0 +1,49 @@
+# *****************************************************************************
+# Copyright (c) 2020, Intel Corporation All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+#     Redistributions of source code must retain the above copyright notice,
+#     this list of conditions and the following disclaimer.
+#
+#     Redistributions in binary form must reproduce the above copyright notice,
+#     this list of conditions and the following disclaimer in the documentation
+#     and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
+# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
+# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
+# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+"""
+Expect Series
+0      one
+1      two
+2    three
+0     four
+1     five
+2      six
+dtype: object
+"""
+import pandas as pd
+from numba import njit
+
+
+@njit
+def series_append():
+    s1 = pd.Series(['one', 'two', 'three'])
+    s2 = pd.Series(['four', 'five', 'six'])
+
+    return s1.append(s2)
+
+
+print(series_append())

examples/series/series_astype.py

@@ -24,11 +24,6 @@
 # EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 # *****************************************************************************
 
-import numpy as np
-import pandas as pd
-from numba import njit
-
-
 """
 Expect Series
 0      3.000000
@@ -38,6 +33,11 @@
 4     92.000000
 dtype: object
 """
+import numpy as np
+import pandas as pd
+from numba import njit
+
+
 @njit
 def series_astype():
     series = pd.Series([3, -10, np.nan, 0, 92])

examples/series/series_cov.py

@@ -0,0 +1,40 @@
+# *****************************************************************************
+# Copyright (c) 2020, Intel Corporation All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+#     Redistributions of source code must retain the above copyright notice,
+#     this list of conditions and the following disclaimer.
+#
+#     Redistributions in binary form must reproduce the above copyright notice,
+#     this list of conditions and the following disclaimer in the documentation
+#     and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
+# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
+# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
+# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+import numpy as np
+import pandas as pd
+from numba import njit
+
+
+@njit
+def series_cov():
+    s1 = pd.Series([3.2, -10, np.nan, 0.23, 9.2])
+    s2 = pd.Series([5., 0, 3.3, np.nan, 9.2])
+
+    return s1.cov(s2)  # Expect value: 44.639...
+
+
+print(series_cov())

examples/series/series_describe.py

@@ -0,0 +1,51 @@
+# *****************************************************************************
+# Copyright (c) 2020, Intel Corporation All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+#     Redistributions of source code must retain the above copyright notice,
+#     this list of conditions and the following disclaimer.
+#
+#     Redistributions in binary form must reproduce the above copyright notice,
+#     this list of conditions and the following disclaimer in the documentation
+#     and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
+# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
+# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
+# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+"""
+Expect Series
+count    5.000000
+mean     4.380000
+std      3.315419
+min      0.000000
+25%      3.300000
+50%      4.400000
+75%      5.000000
+max      9.200000
+dtype: float64
+"""
+import numpy as np
+import pandas as pd
+from numba import njit
+
+
+@njit
+def series_describe():
+    s = pd.Series([5., 0, 3.3, 4.4, 9.2])
+
+    return s.describe()
+
+
+print(series_describe())

examples/series/series_dropna.py

@@ -24,18 +24,18 @@
 # EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 # *****************************************************************************
 
-import numpy as np
-import pandas as pd
-from numba import njit
-
-
 """
 Expect Series
 0    4.0
 2    2.0
 3    1.0
 dtype: float64
 """
+import numpy as np
+import pandas as pd
+from numba import njit
+
+
 @njit
 def series_dropna():
     s = pd.Series([4, np.nan, 2, 1])

examples/series/series_fillna.py

@@ -24,11 +24,6 @@
 # EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 # *****************************************************************************
 
-import numpy as np
-import pandas as pd
-from numba import njit
-
-
 """
 Expect Series
 0    4.0
@@ -37,6 +32,11 @@
 3    1.0
 dtype: float64
 """
+import numpy as np
+import pandas as pd
+from numba import njit
+
+
 @njit
 def series_fillna():
     s = pd.Series([4, np.nan, 2, 1])

examples/series/series_groupby.py

@@ -0,0 +1,44 @@
+# *****************************************************************************
+# Copyright (c) 2020, Intel Corporation All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+#     Redistributions of source code must retain the above copyright notice,
+#     this list of conditions and the following disclaimer.
+#
+#     Redistributions in binary form must reproduce the above copyright notice,
+#     this list of conditions and the following disclaimer in the documentation
+#     and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
+# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
+# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
+# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+"""
+Expect Series
+a    210.0
+b    185.0
+dtype: float64
+"""
+import pandas as pd
+from numba import njit
+
+
+@njit
+def series_groupby():
+    s = pd.Series([390., 350., 30., 20.]).mean()
+
+    return s.groupby(["a", "b", "a", "b"])
+
+
+# print(series_groupby())

examples/series/series_head.py

@@ -24,19 +24,19 @@
 # EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 # *****************************************************************************
 
+"""
+Expected Series
+0    7
+2    6
+4    5
+dtype: int64
+"""
 import pandas as pd
 from numba import njit
 
 
 @njit
 def series_head():
-    """
-    Expected Series
-    0    7
-    2    6
-    4    5
-    dtype: int64
-    """
     s = pd.Series([7, 6, 5, 4, 3, 2, 1], index=[0, 2, 4, 6, 8, 10, 12])
 
     return s.head(3)

examples/series/series_pct_change.py

@@ -0,0 +1,48 @@
+# *****************************************************************************
+# Copyright (c) 2020, Intel Corporation All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+#     Redistributions of source code must retain the above copyright notice,
+#     this list of conditions and the following disclaimer.
+#
+#     Redistributions in binary form must reproduce the above copyright notice,
+#     this list of conditions and the following disclaimer in the documentation
+#     and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
+# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
+# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
+# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+"""
+Expect Series
+0         NaN
+1         NaN
+2   -0.340000
+3         NaN
+4    1.787879
+dtype: float64
+"""
+import numpy as np
+import pandas as pd
+from numba import njit
+
+
+@njit
+def series_pct_change():
+    s = pd.Series([5., 0, 3.3, np.nan, 9.2])
+
+    return s.pct_change(periods=2, fill_method=None, limit=None, freq=None)
+
+
+print(series_pct_change())

examples/series/series_rename.py

@@ -24,19 +24,20 @@
 # EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 # *****************************************************************************
 
-import numpy as np
-import pandas as pd
-from numba import njit
-
-
 """
+Expect Series
 0    0
 1    1
 2    2
 3    3
 4    4
 Name: new_series, dtype: int64
 """
+import numpy as np
+import pandas as pd
+from numba import njit
+
+
 @njit
 def series_rename():
     s = pd.Series(np.arange(5))