From 415e537014d172a45beab98d32353f740c93eb03 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jure=20=C5=A0orn?= Date: Fri, 19 Jun 2020 18:16:10 +0200 Subject: [PATCH] Pandas --- README.md | 139 ++++++++++++++++++++++++++++++++++++----------------- index.html | 133 ++++++++++++++++++++++++++++++++------------------ 2 files changed, 183 insertions(+), 89 deletions(-) diff --git a/README.md b/README.md index fe17a71..3a4e650 100644 --- a/README.md +++ b/README.md @@ -3076,7 +3076,7 @@ from pandas import Series, DataFrame **Ordered dictionary with a name.** ```python ->>> Series([1, 2], index=['x', 'y'], name='a') +>>> sr = Series([1, 2], index=['x', 'y'], name='a') x 1 y 2 Name: a, dtype: int64 @@ -3110,22 +3110,37 @@ Name: a, dtype: int64 = .combine_first() # Adds items that are not yet present (extends). ``` -#### Operations: +#### Aggregations: ```python = .sum/max/mean/idxmax/all() + = () + = .apply/agg() # Apply can only accept strings. +``` + +```python ++-------------+--------+-----------+---------------+ +| | 'sum' | ['sum'] | {'s': 'sum'} | ++-------------+--------+-----------+---------------+ +| sr.apply(…) | | | | +| sr.agg(…) | 3 | sum 3 | s 3 | +| | | | | ++-------------+--------+-----------+---------------+ +``` + +#### Transformations: +```python = .diff/cumsum/rank/pct_change() # …/fillna/ffill/interpolate() - = .apply/agg() = .apply/agg/transform() ``` ```python -+-------------+------------+-----------+--------------+--------+-------------+---------------+ -| | 'sum' | ['sum'] | {'s': 'sum'} | 'rank' | ['rank'] | {'r': 'rank'} | -+-------------+------------+-----------+--------------+--------+-------------+---------------+ -| sr.apply(…) | | | | | rank | | -| sr.agg(…) | 3 | sum 3 | s 3 | x 1 | x 1 | r x 1 | -| | | | | y 2 | y 2 | y 2 | -+-------------+------------+-----------+--------------+--------+-------------+---------------+ ++-------------+--------+-----------+---------------+ +| | 'rank' | ['rank'] | {'r': 'rank'} | ++-------------+--------+-----------+---------------+ +| sr.apply(…) | | rank | | +| sr.agg(…) | x 1 | x 1 | r x 1 | +| sr.trans(…) | y 2 | y 2 | y 2 | ++-------------+--------+-----------+---------------+ ``` ### DataFrame @@ -3168,27 +3183,44 @@ b 3 4 = .melt(id_vars=column_key/s) # Melts on columns. ``` -#### Operations: ```python = .sum/max/mean/idxmax/all() - = .diff/cumsum/rank() # …/pct_change/fillna/ffill/interpolate() = .apply/agg/transform() + = .diff/cumsum/rank() # …/pct_change/fillna/ffill/interpolate() = .apply/agg/transform() = .applymap() # Apply a function to a Dataframe elementwise. ``` * **All operations operate on columns by default. Use `'axis=1'` parameter to process the rows instead.** +#### Apply, Aggregate, Transform: ```python -+-------------+------------+-----------+--------------+--------+-------------+---------------+ -| | 'sum' | ['sum'] | {'x': 'sum'} | 'rank' | ['rank'] | {'x': 'rank'} | -+-------------+------------+-----------+--------------+--------+-------------+---------------+ -| df.apply(…) | | x y | | x y | x y | x | -| df.agg(…) | x 4 | sum 4 6 | x 4 | a 1 1 | rank rank | a 1 | -| df.trans(…) | y 6 | | | b 2 2 | a 1 1 | b 2 | -| | | | | | b 2 2 | | -+-------------+------------+-----------+--------------+--------+-------------+---------------+ +>>> df = DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y']) + x y +a 1 2 +b 3 4 ``` -* **Transform doesen't work with `['sum']` and `{'x': 'sum'}`.** + +```python ++-------------+---------------+---------------+---------------+ +| | 'sum' | ['sum'] | {'x': 'sum'} | ++-------------+---------------+---------------+---------------+ +| df.apply(…) | | x y | | +| df.agg(…) | x 4 | sum 4 6 | x 4 | +| df.trans(…) | y 6 | | | ++-------------+---------------+---------------+---------------+ +``` + +```python ++-------------+---------------+---------------+---------------+ +| | 'rank' | ['rank'] | {'x': 'rank'} | ++-------------+---------------+---------------+---------------+ +| df.apply(…) | x y | x y | x | +| df.agg(…) | a 1 1 | rank rank | a 1 | +| df.trans(…) | b 2 2 | a 1 1 | b 2 | +| | | b 2 2 | | ++-------------+---------------+---------------+---------------+ +``` +* **Transform() doesen't work with `['sum']` and `{'x': 'sum'}`.** #### Merge, Join, Concat: ```python @@ -3253,34 +3285,55 @@ c 6 7 ``` * **Result of an operation is a dataframe with index made up of group keys. Use `'.reset_index()'` to move the index back into it's own column.** -#### Operations: +#### Aggregations: ```python = .sum/max/mean/idxmax/all() - = .diff/cumsum/rank() # …/pct_change/fillna/ffill() = .apply/agg/transform() +``` + +```python ++-------------+------------+-------------+---------------+ +| | 'sum' | ['sum'] | {'x': 'sum'} | ++-------------+------------+-------------+---------------+ +| gb.apply(…) | x y z | | | +| | z | | | +| | 3 1 2 3 | | | +| | 6 11 13 12 | | | ++-------------+------------+-------------+---------------+ +| gb.agg(…) | x y | x y | x | +| | z | sum sum | z | +| | 3 1 2 | z | 3 1 | +| | 6 11 13 | 3 1 2 | 6 11 | +| | | 6 11 13 | | ++-------------+------------+-------------+---------------+ +| gb.trans(…) | x y | | | +| | a 1 2 | | | +| | b 11 13 | | | +| | c 11 13 | | | ++-------------+------------+-------------+---------------+ +``` + +#### Transformations: +```python + = .diff/cumsum/rank() # …/pct_change/fillna/ffill() = .agg/transform() ``` ```python -+-------------+------------+-----------+--------------+--------+-------------+---------------+ -| | 'sum' | ['sum'] | {'x': 'sum'} | 'rank' | ['rank'] | {'x': 'rank'} | -+-------------+------------+-----------+--------------+--------+-------------+---------------+ -| gb.apply(…) | x y z | | | | | | -| | z | | | | | | -| | 3 1 2 3 | | | | | | -| | 6 11 13 12 | | | | | | -+-------------+------------+-----------+--------------+--------+-------------+---------------+ -| gb.agg(…) | x y | x y | x | x y | x y | x | -| | z | sum sum | z | a 1 1 | rank rank | a 1 | -| | 3 1 2 | z | 3 1 | b 1 1 | a 1 1 | b 1 | -| | 6 11 13 | 3 1 2 | 6 11 | c 2 2 | b 1 1 | c 2 | -| | | 6 11 13 | | | c 2 2 | | -+-------------+------------+-----------+--------------+--------+-------------+---------------+ -| gb.trans(…) | x y | | | x y | | | -| | a 1 2 | | | a 1 1 | | | -| | b 11 13 | | | b 1 1 | | | -| | c 11 13 | | | c 1 1 | | | -+-------------+------------+-----------+--------------+--------+-------------+---------------+ ++-------------+------------+-------------+---------------+ +| | 'rank' | ['rank'] | {'x': 'rank'} | ++-------------+------------+-------------+---------------+ +| gb.agg(…) | x y | x y | x | +| | a 1 1 | rank rank | a 1 | +| | b 1 1 | a 1 1 | b 1 | +| | c 2 2 | b 1 1 | c 2 | +| | | c 2 2 | | ++-------------+------------+-------------+---------------+ +| gb.trans(…) | x y | | | +| | a 1 1 | | | +| | b 1 1 | | | +| | c 1 1 | | | ++-------------+------------+-------------+---------------+ ``` ### Rolling @@ -3288,7 +3341,7 @@ c 6 7 = .rolling(window_size) # Also: `min_periods=None, center=False`. = [column_key/s] # Or: .column_key = .sum/max/mean() - = .apply() # Invokes function on every window. + = .apply() # Invokes function on every window. = .aggregate() # Invokes function on every window. ``` diff --git a/index.html b/index.html index b47a375..00c7030 100644 --- a/index.html +++ b/index.html @@ -2613,7 +2613,7 @@ SIZE, MAX_SPEED = 50, P(from pandas import Series, DataFrame -

Series

Ordered dictionary with a name.

>>> Series([1, 2], index=['x', 'y'], name='a')
+
Series
Ordered dictionary with a name.
>>> sr = Series([1, 2], index=['x', 'y'], name='a')
 x    1
 y    2
 Name: a, dtype: int64
@@ -2638,19 +2638,30 @@ Name: a, dtype: int64
 
<Sr> = <Sr>.append(<Sr>)                      # Or: pd.concat(<coll_of_Sr>)
 <Sr> = <Sr>.combine_first(<Sr>)               # Adds items that are not yet present (extends).
 

-
Operations:
<el> = <Sr>.sum/max/mean/idxmax/all()
-<Sr> = <Sr>.diff/cumsum/rank/pct_change()     # …/fillna/ffill/interpolate()
-<el> = <Sr>.apply/agg(<agg_func>)
+
Aggregations:
<el> = <Sr>.sum/max/mean/idxmax/all()
+<el> = <agg_func>(<Sr>)
+<el> = <Sr>.apply/agg(<agg_func>)             # Apply can only accept strings.
+

+
+
+-------------+--------+-----------+---------------+
+|             |  'sum' |  ['sum']  |  {'s': 'sum'} |
++-------------+--------+-----------+---------------+
+| sr.apply(…) |        |           |               |
+| sr.agg(…)   |    3   |   sum 3   |      s  3     |
+|             |        |           |               |
++-------------+--------+-----------+---------------+
+

+
Transformations:
<Sr> = <Sr>.diff/cumsum/rank/pct_change()     # …/fillna/ffill/interpolate()
 <Sr> = <Sr>.apply/agg/transform(<trans_func>)
 

 
-
+-------------+------------+-----------+--------------+--------+-------------+---------------+
-|             |    'sum'   |  ['sum']  | {'s': 'sum'} | 'rank' |  ['rank']   | {'r': 'rank'} |
-+-------------+------------+-----------+--------------+--------+-------------+---------------+
-| sr.apply(…) |            |           |              |        |      rank   |               |
-| sr.agg(…)   |      3     |   sum 3   |     s  3     |  x  1  |   x     1   |    r  x  1    |
-|             |            |           |              |  y  2  |   y     2   |       y  2    |
-+-------------+------------+-----------+--------------+--------+-------------+---------------+
+
+-------------+--------+-----------+---------------+
+|             | 'rank' | ['rank']  | {'r': 'rank'} |
++-------------+--------+-----------+---------------+
+| sr.apply(…) |        |     rank  |               |
+| sr.agg(…)   |  x  1  |  x     1  |    r  x  1    |
+| sr.trans(…) |  y  2  |  y     2  |       y  2    |
++-------------+--------+-----------+---------------+
 

 
DataFrame
Table with labeled rows and columns.
>>> DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y'])
    x  y
@@ -2679,27 +2690,40 @@ b  3  4
 <DF>    = <DF>.transpose()                    # Rotates the table.
 <DF>    = <DF>.melt(id_vars=column_key/s)     # Melts on columns.
 

-
Operations:
<Sr>    = <DF>.sum/max/mean/idxmax/all()
-<DF>    = <DF>.diff/cumsum/rank()             # …/pct_change/fillna/ffill/interpolate()
+
<Sr>    = <DF>.sum/max/mean/idxmax/all()
 <Sr>    = <DF>.apply/agg/transform(<agg_func>)
+<DF>    = <DF>.diff/cumsum/rank()             # …/pct_change/fillna/ffill/interpolate()
 <DF>    = <DF>.apply/agg/transform(<trans_func>)
 <DF>    = <DF>.applymap(<func>)               # Apply a function to a Dataframe elementwise.
-

-
+

 
    
 
  • All operations operate on columns by default. Use 'axis=1' parameter to process the rows instead. 
    • 
 

-
+-------------+------------+-----------+--------------+--------+-------------+---------------+
-|             |    'sum'   |  ['sum']  | {'x': 'sum'} | 'rank' |  ['rank']   | {'x': 'rank'} |
-+-------------+------------+-----------+--------------+--------+-------------+---------------+
-| df.apply(…) |            |      x y  |              |    x y |      x    y |        x      |
-| df.agg(…)   |    x  4    |  sum 4 6  |     x  4     | a  1 1 |   rank rank |     a  1      |
-| df.trans(…) |    y  6    |           |              | b  2 2 | a    1    1 |     b  2      |
-|             |            |           |              |        | b    2    2 |               |
-+-------------+------------+-----------+--------------+--------+-------------+---------------+
+
Apply, Aggregate, Transform:
>>> df = DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y'])
+   x  y
+a  1  2
+b  3  4
+

+
+
+-------------+---------------+---------------+---------------+
+|             |     'sum'     |    ['sum']    | {'x': 'sum'}  |
++-------------+---------------+---------------+---------------+
+| df.apply(…) |               |        x y    |               |
+| df.agg(…)   |     x  4      |    sum 4 6    |     x  4      |
+| df.trans(…) |     y  6      |               |               |
++-------------+---------------+---------------+---------------+
+

+
+-------------+---------------+---------------+---------------+
+|             |    'rank'     |   ['rank']    | {'x': 'rank'} |
++-------------+---------------+---------------+---------------+
+| df.apply(…) |       x  y    |       x    y  |        x      |
+| df.agg(…)   |    a  1  1    |    rank rank  |     a  1      |
+| df.trans(…) |    b  2  2    |  a    1    1  |     b  2      |
+|             |               |  b    2    2  |               |
++-------------+---------------+---------------+---------------+
 

 
    
-
  • Transform doesen't work with ['sum'] and {'x': 'sum'}.
    • 
+
  • Transform() doesen't work with ['sum'] and {'x': 'sum'}.
    • 
 

 
Merge, Join, Concat:
>>> l = DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y'])
    x  y 
@@ -2757,36 +2781,53 @@ c  6  7
 
    
 
  • Result of an operation is a dataframe with index made up of group keys. Use '<DF>.reset_index()' to move the index back into it's own column.
    • 
 

-
Operations:
<DF> = <GB>.sum/max/mean/idxmax/all()
-<DF> = <GB>.diff/cumsum/rank()                # …/pct_change/fillna/ffill()
+
Aggregations:
<DF> = <GB>.sum/max/mean/idxmax/all()
 <DF> = <GB>.apply/agg/transform(<agg_func>)
+

+
+
+-------------+------------+-------------+---------------+
+|             |    'sum'   |   ['sum']   | {'x': 'sum'}  |
++-------------+------------+-------------+---------------+
+| gb.apply(…) |    x  y  z |             |               |
+|             | z          |             |               |
+|             | 3  1  2  3 |             |               |
+|             | 6 11 13 12 |             |               |
++-------------+------------+-------------+---------------+
+| gb.agg(…)   |     x   y  |      x   y  |         x     |
+|             | z          |    sum sum  |     z         |
+|             | 3   1   2  |  z          |     3   1     |
+|             | 6  11  13  |  3   1   2  |     6  11     |
+|             |            |  6  11  13  |               |
++-------------+------------+-------------+---------------+
+| gb.trans(…) |     x   y  |             |               |
+|             | a   1   2  |             |               |
+|             | b  11  13  |             |               |
+|             | c  11  13  |             |               |
++-------------+------------+-------------+---------------+
+

+
Transformations:
<DF> = <GB>.diff/cumsum/rank()                # …/pct_change/fillna/ffill()
 <DF> = <GB>.agg/transform(<trans_func>)
 

 
-
+-------------+------------+-----------+--------------+--------+-------------+---------------+
-|             |    'sum'   |  ['sum']  | {'x': 'sum'} | 'rank' |  ['rank']   | {'x': 'rank'} |
-+-------------+------------+-----------+--------------+--------+-------------+---------------+
-| gb.apply(…) |    x  y  z |           |              |        |             |               |
-|             | z          |           |              |        |             |               |
-|             | 3  1  2  3 |           |              |        |             |               |
-|             | 6 11 13 12 |           |              |        |             |               |
-+-------------+------------+-----------+--------------+--------+-------------+---------------+
-| gb.agg(…)   |     x  y   |     x   y |        x     |    x y |      x    y |         x     |
-|             |  z         |   sum sum |     z        | a  1 1 |   rank rank |      a  1     |
-|             |  3  1  2   | z         |     3  1     | b  1 1 | a    1    1 |      b  1     |
-|             |  6 11 13   | 3   1   2 |     6 11     | c  2 2 | b    1    1 |      c  2     |
-|             |            | 6  11  13 |              |        | c    2    2 |               |
-+-------------+------------+-----------+--------------+--------+-------------+---------------+
-| gb.trans(…) |     x  y   |           |              |    x y |             |               |
-|             |  a  1  2   |           |              | a  1 1 |             |               |
-|             |  b 11 13   |           |              | b  1 1 |             |               |
-|             |  c 11 13   |           |              | c  1 1 |             |               |
-+-------------+------------+-----------+--------------+--------+-------------+---------------+
+
+-------------+------------+-------------+---------------+
+|             |   'rank'   |  ['rank']   | {'x': 'rank'} |
++-------------+------------+-------------+---------------+
+| gb.agg(…)   |     x  y   |      x    y |        x      |
+|             |  a  1  1   |   rank rank |     a  1      |
+|             |  b  1  1   | a    1    1 |     b  1      |
+|             |  c  2  2   | b    1    1 |     c  2      |
+|             |            | c    2    2 |               |
++-------------+------------+-------------+---------------+
+| gb.trans(…) |     x  y   |             |               |
+|             |  a  1  1   |             |               |
+|             |  b  1  1   |             |               |
+|             |  c  1  1   |             |               |
++-------------+------------+-------------+---------------+
 

 
Rolling
<Rl_S/D/G> = <Sr/DF/GB>.rolling(window_size)  # Also: `min_periods=None, center=False`.
 <Rl_S/D>   = <Rl_D/G>[column_key/s]           # Or: <Rl>.column_key
 <Sr/DF/DF> = <Rl_S/D/G>.sum/max/mean()
-<Sr/DF/DF> = <Rl_S/D/G>.apply(<func>)         # Invokes function on every window.
+<Sr/DF/DF> = <Rl_S/D/G>.apply(<agg_func>)     # Invokes function on every window.
 <Sr/DF/DF> = <Rl_S/D/G>.aggregate(<func/str>) # Invokes function on every window.