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5 commits

Author SHA1 Message Date
Xinrong Meng 56c211bd6a [SPARK-36470][PYTHON] Implement CategoricalIndex.map and DatetimeIndex.map
Implement `CategoricalIndex.map` and `DatetimeIndex.map`

`MultiIndex.map` cannot be implemented in the same way as the `map` of other indexes. It should be taken care of separately if necessary.

Mapping values using input correspondence is a common operation that is supported in pandas. We shall support that as well.

Yes. `CategoricalIndex.map` and `DatetimeIndex.map` can be used now.

- CategoricalIndex.map

```py
>>> idx = ps.CategoricalIndex(['a', 'b', 'c'])
>>> idx
CategoricalIndex(['a', 'b', 'c'], categories=['a', 'b', 'c'], ordered=False, dtype='category')

>>> idx.map(lambda x: x.upper())
CategoricalIndex(['A', 'B', 'C'],  categories=['A', 'B', 'C'], ordered=False, dtype='category')

>>> pser = pd.Series([1, 2, 3], index=pd.CategoricalIndex(['a', 'b', 'c'], ordered=True))
>>> idx.map(pser)
CategoricalIndex([1, 2, 3], categories=[1, 2, 3], ordered=True, dtype='category')

>>> idx.map({'a': 'first', 'b': 'second', 'c': 'third'})
CategoricalIndex(['first', 'second', 'third'], categories=['first', 'second', 'third'], ordered=False, dtype='category')
```

- DatetimeIndex.map

```py
>>> pidx = pd.date_range(start="2020-08-08", end="2020-08-10")
>>> psidx = ps.from_pandas(pidx)

>>> mapper_dict = {
...   datetime.datetime(2020, 8, 8): datetime.datetime(2021, 8, 8),
...   datetime.datetime(2020, 8, 9): datetime.datetime(2021, 8, 9),
... }
>>> psidx.map(mapper_dict)
DatetimeIndex(['2021-08-08', '2021-08-09', 'NaT'], dtype='datetime64[ns]', freq=None)

>>> mapper_pser = pd.Series([1, 2, 3], index=pidx)
>>> psidx.map(mapper_pser)
Int64Index([1, 2, 3], dtype='int64')
>>> psidx
DatetimeIndex(['2020-08-08', '2020-08-09', '2020-08-10'], dtype='datetime64[ns]', freq=None)

>>> psidx.map(lambda x: x.strftime("%B %d, %Y, %r"))
Index(['August 08, 2020, 12:00:00 AM', 'August 09, 2020, 12:00:00 AM',
       'August 10, 2020, 12:00:00 AM'],
      dtype='object')
```

Unit tests.

Closes #33756 from xinrong-databricks/other_indexes_map.

Authored-by: Xinrong Meng <xinrong.meng@databricks.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
(cherry picked from commit 0b6af464dc)
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
2021-08-23 10:11:21 +09:00
itholic b8740a1d1e [SPARK-35499][PYTHON] Apply black to pandas API on Spark codes
### What changes were proposed in this pull request?

This PR proposes applying `black` to pandas API on Spark codes, for improving static analysis.

By executing the `./dev/reformat-python` in the spark home directory, all the code of the pandas API on Spark is fixed according to the static analysis rules.

### Why are the changes needed?

This can be reduces the cost of static analysis during development.

It has been used continuously for about a year in the Koalas project and its convenience has been proven.

### Does this PR introduce _any_ user-facing change?

No, it's dev-only.

### How was this patch tested?

Manually reformat the pandas API on Spark codes by running the `./dev/reformat-python`, and checked the `./dev/lint-python` is passed.

Closes #32779 from itholic/SPARK-35499.

Authored-by: itholic <haejoon.lee@databricks.com>
Signed-off-by: Liang-Chi Hsieh <viirya@gmail.com>
2021-06-06 17:30:07 -07:00
HyukjinKwon 7ff9d2e3ee [SPARK-35071][PYTHON] Rename Koalas to pandas-on-Spark in main codes
### What changes were proposed in this pull request?

This PR proposes to rename Koalas to pandas-on-Spark in main codes

### Why are the changes needed?

To have the correct name in PySpark. NOTE that the official name in the main documentation will be pandas APIs on Spark to be extra clear. pandas-on-Spark is not the official term.

### Does this PR introduce _any_ user-facing change?

No, it's master-only change. It changes the docstring and class names.

### How was this patch tested?

Manually tested via:

```bash
./python/run-tests --python-executable=python3 --modules pyspark-pandas
```

Closes #32166 from HyukjinKwon/rename-koalas.

Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2021-04-15 12:48:59 +09:00
Takuya UESHIN 2635c3894f [SPARK-34972][PYTHON] Make pandas-on-Spark doctests work
### What changes were proposed in this pull request?

Now that we merged the Koalas main code into PySpark code base (#32036), we should enable doctests on the Spark's infrastructure.

### Why are the changes needed?

Currently the pandas-on-Spark modules are not tested at all.
We should enable doctests first, and we will port other unit tests separately later.

### Does this PR introduce _any_ user-facing change?

No.

### How was this patch tested?

Enabled the whole doctests.

Closes #32069 from ueshin/issues/SPARK-34972/pyspark-pandas_doctests.

Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2021-04-07 20:50:41 +09:00
itholic caf04f9b77 [SPARK-34890][PYTHON] Port/integrate Koalas main codes into PySpark
### What changes were proposed in this pull request?

As a first step of [SPARK-34849](https://issues.apache.org/jira/browse/SPARK-34849), this PR proposes porting the Koalas main code into PySpark.

This PR contains minimal changes to the existing Koalas code as follows:
1. `databricks.koalas` -> `pyspark.pandas`
2. `from databricks import koalas as ks` -> `from pyspark import pandas as pp`
3. `ks.xxx -> pp.xxx`

Other than them:
1. Added a line to `python/mypy.ini` in order to ignore the mypy test. See related issue at [SPARK-34941](https://issues.apache.org/jira/browse/SPARK-34941).
2. Added a comment to several lines in several files to ignore the flake8 F401. See related issue at [SPARK-34943](https://issues.apache.org/jira/browse/SPARK-34943).

When this PR is merged, all the features that were previously used in [Koalas](https://github.com/databricks/koalas) will be available in PySpark as well.

Users can access to the pandas API in PySpark as below:

```python
>>> from pyspark import pandas as pp
>>> ppdf = pp.DataFrame({"A": [1, 2, 3], "B": [15, 20, 25]})
>>> ppdf
   A   B
0  1  15
1  2  20
2  3  25
```

The existing "options and settings" in Koalas are also available in the same way:

```python
>>> from pyspark.pandas.config import set_option, reset_option, get_option
>>> ppser1 = pp.Series([1, 2, 3])
>>> ppser2 = pp.Series([3, 4, 5])
>>> ppser1 + ppser2
Traceback (most recent call last):
...
ValueError: Cannot combine the series or dataframe because it comes from a different dataframe. In order to allow this operation, enable 'compute.ops_on_diff_frames' option.

>>> set_option("compute.ops_on_diff_frames", True)
>>> ppser1 + ppser2
0    4
1    6
2    8
dtype: int64
```

Please also refer to the [API Reference](https://koalas.readthedocs.io/en/latest/reference/index.html) and [Options and Settings](https://koalas.readthedocs.io/en/latest/user_guide/options.html) for more detail.

**NOTE** that this PR intentionally ports the main codes of Koalas first almost as are with minimal changes because:
- Koalas project is fairly large. Making some changes together for PySpark will make it difficult to review the individual change.
    Koalas dev includes multiple Spark committers who will review. By doing this, the committers will be able to more easily and effectively review and drive the development.
- Koalas tests and documentation require major changes to make it look great together with PySpark whereas main codes do not require.
- We lately froze the Koalas codebase, and plan to work together on the initial porting. By porting the main codes first as are, it unblocks the Koalas dev to work on other items in parallel.

I promise and will make sure on:
- Rename Koalas to PySpark pandas APIs and/or pandas-on-Spark accordingly in documentation, and the docstrings and comments in the main codes.
- Triage APIs to remove that don’t make sense when Koalas is in PySpark

The documentation changes will be tracked in [SPARK-34885](https://issues.apache.org/jira/browse/SPARK-34885), the test code changes will be tracked in [SPARK-34886](https://issues.apache.org/jira/browse/SPARK-34886).

### Why are the changes needed?

Please refer to:
- [[DISCUSS] Support pandas API layer on PySpark](http://apache-spark-developers-list.1001551.n3.nabble.com/DISCUSS-Support-pandas-API-layer-on-PySpark-td30945.html)
- [[VOTE] SPIP: Support pandas API layer on PySpark](http://apache-spark-developers-list.1001551.n3.nabble.com/VOTE-SPIP-Support-pandas-API-layer-on-PySpark-td30996.html)

### Does this PR introduce _any_ user-facing change?

Yes, now users can use the pandas APIs on Spark

### How was this patch tested?

Manually tested for exposed major APIs and options as described above.

### Koalas contributors

Koalas would not have been possible without the following contributors:

ueshin
HyukjinKwon
rxin
xinrong-databricks
RainFung
charlesdong1991
harupy
floscha
beobest2
thunterdb
garawalid
LucasG0
shril
deepyaman
gioa
fwani
90jam
thoo
AbdealiJK
abishekganesh72
gliptak
DumbMachine
dvgodoy
stbof
nitlev
hjoo
gatorsmile
tomspur
icexelloss
awdavidson
guyao
akhilputhiry
scook12
patryk-oleniuk
tracek
dennyglee
athena15
gstaubli
WeichenXu123
hsubbaraj
lfdversluis
ktksq
shengjh
margaret-databricks
LSturtew
sllynn
manuzhang
jijosg
sadikovi

Closes #32036 from itholic/SPARK-34890.

Authored-by: itholic <haejoon.lee@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2021-04-06 12:42:39 +09:00