Getting a value from DataFrame based on other column value (PySpark)

Question

I have a Spark dataframe which I want to get the statistics

stats_df = df.describe(['mycol'])
stats_df.show()

+-------+------------------+
|summary|             mycol|
+-------+------------------+
|  count|               300|
|   mean|              2243|
| stddev|  319.419860456123|
|    min|              1400|
|    max|              3100|
+-------+------------------+

How do I extract the values of min and max in mycol using the summary min max column values? How do I do it by number index?

Answer 1

Ok let's consider the following example :

from pyspark.sql.functions import rand, randn
df = sqlContext.range(1, 1000).toDF('mycol')
df.describe().show()
# +-------+-----------------+
# |summary|            mycol|
# +-------+-----------------+
# |  count|              999|
# |   mean|            500.0|
# | stddev|288.5307609250702|
# |    min|                1|
# |    max|              999|
# +-------+-----------------+

If you want to access the row concerning stddev, per example, you'll just need to convert it into an RDD, collect it and convert it into a dictionary as following :

stats = dict(df.describe().map(lambda r : (r.summary,r.mycol)).collect())
print(stats['stddev'])
# 288.5307609250702

Answer 2

您可以轻松地从该数据帧上的选择中分配变量。

x = stats_df.select('mycol').where('summary' == 'min')