本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。

# MonthName 類別
<a name="aws-glue-api-pyspark-transforms-MonthName"></a>

 `MonthName` 轉換會從代表日期的字串建立新的資料欄，其中包含月份名稱。

## 範例
<a name="pyspark-MonthName-examples"></a>

```
from pyspark.context import SparkContext
from pyspark.sql import SparkSession
from awsgluedi.transforms import *

sc = SparkContext()
spark = SparkSession(sc)

spark.conf.set("spark.sql.legacy.timeParserPolicy", "LEGACY")

input_df = spark.createDataFrame(
    [
        ("20-2018-12",),
        ("2018-20-12",),
        ("20182012",),
        ("12202018",),
        ("20122018",),
        ("20-12-2018",),
        ("12/20/2018",),
        ("02/02/02",),
        ("02 02 2009",),
        ("02/02/2009",),
        ("August/02/2009",),
        ("02/june/2009",),
        ("02/2020/june",),
        ("2013-02-21 06:35:45.658505",),
        ("August 02 2009",),
        ("2013/02/21",),
        (None,),
    ],
    ["column_1"],
)

try:
    df_output = datetime_functions.MonthName.apply(
        data_frame=input_df,
        spark_context=sc,
        source_column="column_1",
        target_column="target_column"
    )
    df_output.show()
except:
    print("Unexpected Error happened ")
    raise
```

## Output
<a name="pyspark-MonthName-output"></a>

 輸出將是：

```
```
+------------+------------+
| column_1|target_column|
+------------+------------+
|20-2018-12 | December |
|2018-20-12 | null |
| 20182012| null |
| 12202018| null |
| 20122018| null |
|20-12-2018 | December |
|12/20/2018 | December |
| 02/02/02 | February |
|02 02 2009 | February |
|02/02/2009 | February |
|August/02/2009| August |
|02/june/2009| null |
|02/2020/june| null |
|2013-02-21 06:35:45.658505| February |
|August 02 2009| August |
| 2013/02/21| February |
| null | null |
+------------+------------+
```
```

 `MonthName` 轉換會將 `source\_column` 作為 `"column\_1"`，並將 `target\_column` 作為 `"target\_column"`。其會嘗試從 `"column\_1"` 資料欄中的日期/時間字串中擷取月份名稱，並將其放在 `"target\_column"` 資料欄中。如果日期/時間字串的格式無法辨識或無法剖析，則 `"target\_column"` 值會設定為 `null`。

 轉換會從各種日期/時間格式成功擷取月份名稱，例如 "20-12-2018"、"12/20/2018"、"02/02/2009"、"2013-02-21 06:35:45.658505" 和 "August 02 2009"。

## 方法
<a name="aws-glue-api-pyspark-transforms-MonthName-_methods"></a>
+ [\_\_call\_\_](#aws-glue-api-pyspark-transforms-MonthName-__call__)
+ [apply](#aws-glue-api-crawler-pyspark-transforms-MonthName-apply)
+ [name](#aws-glue-api-crawler-pyspark-transforms-MonthName-name)
+ [describeArgs](#aws-glue-api-crawler-pyspark-transforms-MonthName-describeArgs)
+ [describeReturn](#aws-glue-api-crawler-pyspark-transforms-MonthName-describeReturn)
+ [describeTransform](#aws-glue-api-crawler-pyspark-transforms-MonthName-describeTransform)
+ [describeErrors](#aws-glue-api-crawler-pyspark-transforms-MonthName-describeErrors)
+ [describe](#aws-glue-api-crawler-pyspark-transforms-MonthName-describe)

## \_\_call\_\_(spark\_context, data\_frame, target\_column, source\_column=None, value=None)
<a name="aws-glue-api-pyspark-transforms-MonthName-__call__"></a>

 `MonthName` 轉換會從代表日期的字串建立新的資料欄，其中包含月份名稱。
+ `source_column` – 現有資料欄的名稱。
+ `value` – 要評估的字元字串。
+ `target_column` – 新建立資料欄的名稱。

## apply(cls, \*args, \*\*kwargs)
<a name="aws-glue-api-crawler-pyspark-transforms-MonthName-apply"></a>

繼承自 `GlueTransform` [apply](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-apply)。

## name(cls)
<a name="aws-glue-api-crawler-pyspark-transforms-MonthName-name"></a>

繼承自 `GlueTransform` [name](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-name)。

## describeArgs(cls)
<a name="aws-glue-api-crawler-pyspark-transforms-MonthName-describeArgs"></a>

繼承自 `GlueTransform` [describeArgs](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-describeArgs)。

## describeReturn(cls)
<a name="aws-glue-api-crawler-pyspark-transforms-MonthName-describeReturn"></a>

繼承自 `GlueTransform` [describeReturn](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-describeReturn)。

## describeTransform(cls)
<a name="aws-glue-api-crawler-pyspark-transforms-MonthName-describeTransform"></a>

繼承自 `GlueTransform` [describeTransform](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-describeTransform)。

## describeErrors(cls)
<a name="aws-glue-api-crawler-pyspark-transforms-MonthName-describeErrors"></a>

繼承自 `GlueTransform` [describeErrors](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-describeErrors)。

## describe(cls)
<a name="aws-glue-api-crawler-pyspark-transforms-MonthName-describe"></a>

繼承自 `GlueTransform` [describe](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-describe)。