为每个需要翻译的列创建一个case语句。
下面是两列GEN和GEO的示例：

from pyspark.sql import functions as F

df = <input data>

translations = [
    ('GEN', {1: 'Female', 2: 'Male'}),
    ('GEO', {1: 'Ryga', 2: 'Others'})
]

df1 = df
for translation in translations:
    stmt = f'case {translation[0]}'
    for (k,v) in translation[1].items():
      stmt = stmt + f' when {k} then "{v}"'
    stmt = stmt + ' end'
    df1 = df1.withColumn(translation[0], F.expr(stmt))

df1.show()

字符串
输出量：

+------+---+------+------+----+----+---+---+---+
|RespID|AGE|   GEO|   GEN|PROD|BRND| Q1| Q2| Q3|
+------+---+------+------+----+----+---+---+---+
|     1|  1|  Ryga|Female|   3|   3|  4|  1|  6|
|     2|  1|Others|  Male|   2|   1|  1|  4|  9|
|     3|  4|Others|  Male|   1|   1|  3|  4|  6|
|     4|  1|  Ryga|  Male|   3|   2|  7|  4|  3|
|     5|  2|  Ryga|Female|   3|   2|  1|  4|  3|
|     6|  1|  Ryga|  Male|   2|   3|  2|  4|  2|
|     7|  2|Others|  Male|   3|   3|  7|  2| 10|
|     8|  4|Others|Female|   1|   1|  4|  2|  6|
|     9|  3|  Ryga|  Male|   2|   2|  4|  3|  9|
|    10|  1|Others|Female|   1|   1|  7|  7|  7|
+------+---+------+------+----+----+---+---+---+

型
翻译列表可以根据需要扩展到其他列。