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Working on Pandas
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‎README.md‎

Lines changed: 49 additions & 52 deletions
Original file line numberDiff line numberDiff line change
@@ -3111,13 +3111,12 @@ Name: a, dtype: int64
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<Sr>.update(<Sr>) # Updates items that are already present.
31123112
```
31133113

3114-
#### Apply, Aggregate, Transform:
3114+
#### Aggregate, Transform, Map:
31153115
```python
31163116
<el> = <Sr>.sum/max/mean/idxmax/all() # Or: <Sr>.aggregate(<agg_func>)
3117-
<Sr> = <Sr>.rank/diff/cumsum/pct_change() # Or: <Sr>.agg/transform(<trans_func>)
3117+
<Sr> = <Sr>.rank/diff/cumsum/ffill/interpl() # Or: <Sr>.agg/transform(<trans_func>)
31183118
<Sr> = <Sr>.fillna(<el>) # Or: <Sr>.apply/agg/transform/map(<map_func>)
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```
3120-
* **Also: `'ffill()'` and `'interpolate()'`.**
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* **The way `'aggregate()'` and `'transform()'` find out whether a function accepts an element or the whole Series is by passing it a single value at first and if it raises an error, then they pass it the whole Series.**
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```python
@@ -3128,23 +3127,22 @@ dtype: int64
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```
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31303129
```python
3131-
+-------------+---------------+---------------+---------------+
3132-
| | 'sum' | ['sum'] | {'s': 'sum'} |
3133-
+-------------+---------------+---------------+---------------+
3134-
| sr.apply(…) | | | |
3135-
| sr.agg(…) | 3 | sum 3 | s 3 |
3136-
| | | | |
3137-
+-------------+---------------+---------------+---------------+
3130+
┏━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┓
3131+
┃ │ 'sum' │ ['sum'] │ {'s': 'sum'} ┃
3132+
┠─────────────┼─────────────┼─────────────┼───────────────┨
3133+
┃ sr.apply(…) │ 3 │ sum 3 │ s 3 ┃
3134+
┃ sr.agg(…) │ │ │ ┃
3135+
┗━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┛
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```
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```python
3141-
+-------------+---------------+---------------+---------------+
3142-
| | 'rank' | ['rank'] | {'r': 'rank'} |
3143-
+-------------+---------------+---------------+---------------+
3144-
| sr.apply(…) | | rank | |
3145-
| sr.agg(…) | x 1 | x 1 | r x 1 |
3146-
| sr.trans(…) | y 2 | y 2 | y 2 |
3147-
+-------------+---------------+---------------+---------------+
3139+
┏━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┓
3140+
┃ │ 'rank' │ ['rank'] │ {'r': 'rank'} ┃
3141+
┠─────────────┼─────────────┼─────────────┼───────────────┨
3142+
┃ sr.apply(…) │ │ rank │ ┃
3143+
┃ sr.agg(…) │ x 1 │ x 1 │ r x 1 ┃
3144+
┃ sr.trans(…) │ y 2 │ y 2 │ y 2 ┃
3145+
┗━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┛
31483146
```
31493147

31503148
### DataFrame
@@ -3201,7 +3199,7 @@ c 6 7
32013199

32023200
```python
32033201
┏━━━━━━━━━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━┯━━━━━━━━━━━━━━━━━━━━━━━━━━┓
3204-
┃ how/join │ 'outer' │ 'inner' │ 'left' │ description ┃
3202+
┃ how/join │ 'outer' │ 'inner' │ 'left' │ description ┃
32053203
┠────────────────────────┼───────────────┼────────────┼────────────┼──────────────────────────┨
32063204
┃ l.merge(r, on='y', │ x y z │ x y z │ x y z │ Joins/merges on column. ┃
32073205
┃ how=…) │ 0 1 2 . │ 3 4 5 │ 1 2 . │ Also accepts left_on and ┃
@@ -3231,13 +3229,12 @@ c 6 7
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┗━━━━━━━━━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━━━━━━━━━━━┛
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```
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3234-
#### Apply, Aggregate, Transform:
3232+
#### Aggregate, Transform, Map:
32353233
```python
32363234
<Sr> = <DF>.sum/max/mean/idxmax/all() # Or: <DF>.apply/agg/transform(<agg_func>)
3237-
<DF> = <DF>.rank/diff/cumsum/pct_change() # Or: <DF>.apply/agg/transform(<trans_func>)
3235+
<DF> = <DF>.rank/diff/cumsum/ffill/interpl() # Or: <DF>.apply/agg/transform(<trans_func>)
32383236
<DF> = <DF>.fillna(<el>) # Or: <DF>.applymap(<map_func>)
32393237
```
3240-
* **Also: `'ffill()'` and `'interpolate()'`.**
32413238
* **All operations operate on columns by default. Use `'axis=1'` parameter to process the rows instead.**
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32433240
```python
@@ -3248,24 +3245,24 @@ b 3 4
32483245
```
32493246

32503247
```python
3251-
+-------------+---------------+---------------+---------------+
3252-
| | 'sum' | ['sum'] | {'x': 'sum'} |
3253-
+-------------+---------------+---------------+---------------+
3254-
| df.apply(…) | | x y | |
3255-
| df.agg(…) | x 4 | sum 4 6 | x 4 |
3256-
| | y 6 | | |
3257-
+-------------+---------------+---------------+---------------+
3248+
┏━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┓
3249+
┃ │ 'sum' │ ['sum'] │ {'x': 'sum'} ┃
3250+
┠─────────────┼─────────────┼─────────────┼───────────────┨
3251+
┃ df.apply(…) │ │ x y │ ┃
3252+
┃ df.agg(…) │ x 4 │ sum 4 6 │ x 4 ┃
3253+
┃ │ y 6 │ │ ┃
3254+
┗━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┛
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```
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32603257
```python
3261-
+-------------+---------------+---------------+---------------+
3262-
| | 'rank' | ['rank'] | {'x': 'rank'} |
3263-
+-------------+---------------+---------------+---------------+
3264-
| df.apply(…) | x y | x y | x |
3265-
| df.agg(…) | a 1 1 | rank rank | a 1 |
3266-
| df.trans(…) | b 2 2 | a 1 1 | b 2 |
3267-
| | | b 2 2 | |
3268-
+-------------+---------------+---------------+---------------+
3258+
┏━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┓
3259+
┃ │ 'rank' │ ['rank'] │ {'x': 'rank'} ┃
3260+
┠─────────────┼─────────────┼─────────────┼───────────────┨
3261+
┃ df.apply(…) │ x y │ x y │ x ┃
3262+
┃ df.agg(…) │ a 1 1 │ rank rank │ a 1 ┃
3263+
┃ df.trans(…) │ b 2 2 │ a 1 1 │ b 2 ┃
3264+
┃ │ │ b 2 2 │ ┃
3265+
┗━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┛
32693266
```
32703267

32713268
#### Encode, Decode:
@@ -3284,7 +3281,7 @@ b 3 4
32843281
```
32853282

32863283
### GroupBy
3287-
**Object that groups together rows of a dataframe based on the value of passed column.**
3284+
**Object that groups together rows of a dataframe based on the value of the passed column.**
32883285

32893286
```python
32903287
>>> df = DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 6]], index=list('abc'), columns=list('xyz'))
@@ -3302,7 +3299,7 @@ c 7 8
33023299
<DF> = <GB>.get_group(group_key) # Selects a group by value of grouping column.
33033300
```
33043301

3305-
#### Apply, Aggregate, Transform:
3302+
#### Aggregate, Transform, Map:
33063303
```python
33073304
<DF> = <GB>.sum/max/mean/idxmax/all() # Or: <GB>.apply/agg(<agg_func>)
33083305
<DF> = <GB>.rank/diff/cumsum/ffill() # Or: <GB>.aggregate(<trans_func>)
@@ -3318,20 +3315,20 @@ c 7 8
33183315
```
33193316

33203317
```python
3321-
+-------------+-------------+-------------+-------------+---------------+
3322-
| | 'sum' | 'rank' | ['rank'] | {'x': 'rank'} |
3323-
+-------------+-------------+-------------+-------------+---------------+
3324-
| gb.agg(…) | x y | x y | x y | x |
3325-
| | z | a 1 1 | rank rank | a 1 |
3326-
| | 3 1 2 | b 1 1 | a 1 1 | b 1 |
3327-
| | 6 11 13 | c 2 2 | b 1 1 | c 2 |
3328-
| | | | c 2 2 | |
3329-
+-------------+-------------+-------------+-------------+---------------+
3330-
| gb.trans(…) | x y | x y | | |
3331-
| | a 1 2 | a 1 1 | | |
3332-
| | b 11 13 | b 1 1 | | |
3333-
| | c 11 13 | c 1 1 | | |
3334-
+-------------+-------------+-------------+-------------+---------------+
3318+
┏━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┓
3319+
┃ │ 'sum' │ 'rank' │ ['rank'] │ {'x': 'rank'} ┃
3320+
┠─────────────┼─────────────┼─────────────┼─────────────┼───────────────┨
3321+
┃ gb.agg(…) │ x y │ x y │ x y │ x ┃
3322+
┃ │ z │ a 1 1 │ rank rank │ a 1 ┃
3323+
┃ │ 3 1 2 │ b 1 1 │ a 1 1 │ b 1 ┃
3324+
┃ │ 6 11 13 │ c 2 2 │ b 1 1 │ c 2 ┃
3325+
┃ │ │ │ c 2 2 │ ┃
3326+
┠─────────────┼─────────────┼─────────────┼─────────────┼───────────────┨
3327+
┃ gb.trans(…) │ x y │ x y │ │ ┃
3328+
┃ │ a 1 2 │ a 1 1 │ │ ┃
3329+
┃ │ b 11 13 │ b 1 1 │ │ ┃
3330+
┃ │ c 11 13 │ c 1 1 │ │ ┃
3331+
┗━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┛
33353332
```
33363333

33373334
### Rolling

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