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‎README.md‎

Lines changed: 42 additions & 42 deletions
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@@ -3231,7 +3231,7 @@ plt.show() # Displays the plot. Also plt.sav
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**Table with labeled rows and columns.**
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```python
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>>> l = pd.DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y']); l
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>>> df = pd.DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y']); df
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x y
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a 1 2
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b 3 4
@@ -3251,7 +3251,7 @@ b 3 4
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```python
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<S/DF> = <DF>[col_key/s] # Or: <DF>.<col_key>
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<DF> = <DF>[row_bools] # Keeps rows as specified by bools.
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<DF> = <DF>[<S_of_bools>] # Filters rows. For example `df[df.x > 1]`.
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<DF> = <DF>[<DF_of_bools>] # Assigns NaN to items that are False in bools.
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```
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@@ -3270,7 +3270,7 @@ b 3 4
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```python
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<DF> = <DF>.head/tail/sample(<int>) # Returns first, last, or random n rows.
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<DF> = <DF>.describe() # Describes columns. Also info(), corr(), shape.
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<DF> = <DF>.query('<query>') # Filters rows with e.g. 'col_1 == val_1 and …'.
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<DF> = <DF>.query('<query>') # Filters rows. For example `df.query('x > 1')`.
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```
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```python
@@ -3280,37 +3280,37 @@ plt.show() # Displays the plot. Also plt.sav
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#### DataFrame — Merge, Join, Concat:
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```python
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>>> r = pd.DataFrame([[4, 5], [6, 7]], index=['b', 'c'], columns=['y', 'z']); r
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>>> df_2 = pd.DataFrame([[4, 5], [6, 7]], index=['b', 'c'], columns=['y', 'z']); df_2
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y z
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b 4 5
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c 6 7
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```
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```text
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+------------------------+---------------+------------+------------+--------------------------+
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| | 'outer' | 'inner' | 'left' | Description |
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+------------------------+---------------+------------+------------+--------------------------+
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| l.merge(r, on='y', | x y z | x y z | x y z | Merges on column if 'on' |
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| how=…) | 0 1 2 . | 3 4 5 | 1 2 . | or 'left/right_on' are |
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| | 1 3 4 5 | | 3 4 5 | set, else on shared cols.|
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| | 2 . 6 7 | | | Uses 'inner' by default. |
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+------------------------+---------------+------------+------------+--------------------------+
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| l.join(r, lsuffix='l', | x yl yr z | | x yl yr z | Merges on row keys. |
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| rsuffix='r', | a 1 2 . . | x yl yr z | 1 2 . . | Uses 'left' by default. |
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| how=…) | b 3 4 4 5 | 3 4 4 5 | 3 4 4 5 | If r is a Series, it is |
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| | c . . 6 7 | | | treated as a column. |
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+------------------------+---------------+------------+------------+--------------------------+
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| pd.concat([l, r], | x y z | y | | Adds rows at the bottom. |
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| axis=0, | a 1 2 . | 2 | | Uses 'outer' by default. |
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| join=…) | b 3 4 . | 4 | | A Series is treated as a |
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| | b . 4 5 | 4 | | column. To add a row use |
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| | c . 6 7 | 6 | | pd.concat([l, DF([s])]). |
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+------------------------+---------------+------------+------------+--------------------------+
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| pd.concat([l, r], | x y y z | | | Adds columns at the |
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| axis=1, | a 1 2 . . | x y y z | | right end. Uses 'outer' |
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| join=…) | b 3 4 4 5 | 3 4 4 5 | | by default. A Series is |
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| | c . . 6 7 | | | treated as a column. |
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+------------------------+---------------+------------+------------+--------------------------+
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+-----------------------+---------------+------------+------------+---------------------------+
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| | 'outer' | 'inner' | 'left' | Description |
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+-----------------------+---------------+------------+------------+---------------------------+
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| df.merge(df_2, | x y z | x y z | x y z | Merges on column if 'on' |
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| on='y', | 0 1 2 . | 3 4 5 | 1 2 . | or 'left/right_on' are |
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| how=…) | 1 3 4 5 | | 3 4 5 | set, else on shared cols. |
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| | 2 . 6 7 | | | Uses 'inner' by default. |
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+-----------------------+---------------+------------+------------+---------------------------+
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| df.join(df_2, | x yl yr z | | x yl yr z | Merges on row keys. |
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| lsuffix='l', | a 1 2 . . | x yl yr z | 1 2 . . | Uses 'left' by default. |
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| rsuffix='r', | b 3 4 4 5 | 3 4 4 5 | 3 4 4 5 | If r is a Series, it is |
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| how=…) | c . . 6 7 | | | treated as a column. |
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+-----------------------+---------------+------------+------------+---------------------------+
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| pd.concat([df, df_2], | x y z | y | | Adds rows at the bottom. |
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| axis=0, | a 1 2 . | 2 | | Uses 'outer' by default. |
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| join=…) | b 3 4 . | 4 | | A Series is treated as a |
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| | b . 4 5 | 4 | | column. To add a row use |
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| | c . 6 7 | 6 | | pd.concat([df, DF([s])]). |
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+-----------------------+---------------+------------+------------+---------------------------+
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| pd.concat([df, df_2], | x y y z | | | Adds columns at the |
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| axis=1, | a 1 2 . . | x y y z | | right end. Uses 'outer' |
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| join=…) | b 3 4 4 5 | 3 4 4 5 | | by default. A Series is |
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| | c . . 6 7 | | | treated as a column. |
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+-----------------------+---------------+------------+------------+---------------------------+
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```
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#### DataFrame — Aggregate, Transform, Map:
@@ -3321,23 +3321,23 @@ c 6 7
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```
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```text
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+----------------+---------------+---------------+---------------+
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| | 'sum' | ['sum'] | {'x': 'sum'} |
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+----------------+---------------+---------------+---------------+
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| l.apply(…) | x 4 | x y | x 4 |
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| l.agg(…) | y 6 | sum 4 6 | |
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+----------------+---------------+---------------+---------------+
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+-----------------+---------------+---------------+---------------+
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| | 'sum' | ['sum'] | {'x': 'sum'} |
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+-----------------+---------------+---------------+---------------+
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| df.apply(…) | x 4 | x y | x 4 |
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| df.agg(…) | y 6 | sum 4 6 | |
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+-----------------+---------------+---------------+---------------+
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```
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```text
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+----------------+---------------+---------------+---------------+
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| | 'rank' | ['rank'] | {'x': 'rank'} |
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+----------------+---------------+---------------+---------------+
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| l.apply(…) | | x y | |
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| l.agg(…) | x y | rank rank | x |
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| l.transform(…) | a 1.0 1.0 | a 1.0 1.0 | a 1.0 |
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| | b 2.0 2.0 | b 2.0 2.0 | b 2.0 |
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+----------------+---------------+---------------+---------------+
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+-----------------+---------------+---------------+---------------+
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| | 'rank' | ['rank'] | {'x': 'rank'} |
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+-----------------+---------------+---------------+---------------+
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| df.apply(…) | | x y | |
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| df.agg(…) | x y | rank rank | x |
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| df.transform(…) | a 1.0 1.0 | a 1.0 1.0 | a 1.0 |
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| | b 2.0 2.0 | b 2.0 2.0 | b 2.0 |
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+-----------------+---------------+---------------+---------------+
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```
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* **All methods operate on columns by default. Pass `'axis=1'` to process the rows instead.**
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* **Fifth result's columns are indexed with a multi-index. This means we need a tuple of column keys to specify a column: `'<DF>.loc[row_key, (col_key_1, col_key_2)]'`.**

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