Convert spark DataFrame column to python list

问题:

I work on a dataframe with two column, mvv and count.

+---+-----+
|mvv|count|
+---+-----+
| 1 |  5  |
| 2 |  9  |
| 3 |  3  |
| 4 |  1  |

i would like to obtain two list containing mvv values and count value. Something like

mvv = [1,2,3,4]
count = [5,9,3,1]

So, I tried the following code: The first line should return a python list of row. I wanted to see the first value:

mvv_list = mvv_count_df.select('mvv').collect()
firstvalue = mvv_list[0].getInt(0)

But I get an error message with the second line:

AttributeError: getInt

回答1:

See, why this way that you are doing is not working. First, you are trying to get integer from a Row Type, the output of your collect is like this:

>>> mvv_list = mvv_count_df.select('mvv').collect()
>>> mvv_list[0]
Out: Row(mvv=1)

If you take something like this:

>>> firstvalue = mvv_list[0].mvv
Out: 1

You will get the mvv value. If you want all the information of the array you can take something like this:

>>> mvv_array = [int(row.mvv) for row in mvv_list.collect()]
>>> mvv_array
Out: [1,2,3,4]

But if you try the same for the other column, you get:

>>> mvv_count = [int(row.count) for row in mvv_list.collect()]
Out: TypeError: int() argument must be a string or a number, not 'builtin_function_or_method'

This happens because count is a built-in method. And the column has the same name as count. A workaround to do this is change the column name of count to _count:

>>> mvv_list = mvv_list.selectExpr("mvv as mvv", "count as _count")
>>> mvv_count = [int(row._count) for row in mvv_list.collect()]

But this workaround is not needed, as you can access the column using the dictionary syntax:

>>> mvv_array = [int(row['mvv']) for row in mvv_list.collect()]
>>> mvv_count = [int(row['count']) for row in mvv_list.collect()]

And it will finally work!

回答2:

Following one liner gives the list you want.

mvv = mvv_count_df.select("mvv").rdd.flatMap(lambda x: x).collect()

回答3:

This will give you all the elements as a list.

mvv_list = list(
    mvv_count_df.select('mvv').toPandas()['mvv']
)

回答4:

The following code will help you

mvv_count_df.select('mvv').rdd.map(lambda row : row[0]).collect()

回答5:

On my data I got these benchmarks:

>>> data.select(col).rdd.flatMap(lambda x: x).collect()

0.52 sec

>>> [row[col] for row in data.collect()]

0.271 sec

>>> list(data.select(col).toPandas()[col])

0.427 sec

The result is the same

回答6:

If you get the error below :

AttributeError: 'list' object has no attribute 'collect'

This code will solve your issues :

mvv_list = mvv_count_df.select('mvv').collect()

mvv_array = [int(i.mvv) for i in mvv_list]