Mixing
Getting value in a dataframe in PySpark
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I have the below dataframe and I'm trying to get the value 3097 as a int, e.g. storing it in a python variable to manipulate it, multiply it by another int etc.
I've managed to get the row, but I don't even now if it's a good way to do it and I still can't have the value as a int.
data.groupBy("card_bank", "failed").count().filter(data["failed"] == "true").collect()
python apache-spark pyspark
asked Jan 3 at 9:57
LaSulLaSul
615321
add a comment |
I have the below dataframe and I'm trying to get the value 3097 as a int, e.g. storing it in a python variable to manipulate it, multiply it by another int etc.
I've managed to get the row, but I don't even now if it's a good way to do it and I still can't have the value as a int.
data.groupBy("card_bank", "failed").count().filter(data["failed"] == "true").collect()
python apache-spark pyspark
asked Jan 3 at 9:57
LaSulLaSul
615321
add a comment |
I have the below dataframe and I'm trying to get the value 3097 as a int, e.g. storing it in a python variable to manipulate it, multiply it by another int etc.
I've managed to get the row, but I don't even now if it's a good way to do it and I still can't have the value as a int.
data.groupBy("card_bank", "failed").count().filter(data["failed"] == "true").collect()
python apache-spark pyspark
asked Jan 3 at 9:57
LaSulLaSul
615321
I have the below dataframe and I'm trying to get the value 3097 as a int, e.g. storing it in a python variable to manipulate it, multiply it by another int etc.
I've managed to get the row, but I don't even now if it's a good way to do it and I still can't have the value as a int.
data.groupBy("card_bank", "failed").count().filter(data["failed"] == "true").collect()
python apache-spark pyspark
python apache-spark pyspark
asked Jan 3 at 9:57
LaSulLaSul
615321
asked Jan 3 at 9:57
LaSulLaSul
615321
asked Jan 3 at 9:57
LaSulLaSul
615321
asked Jan 3 at 9:57
LaSulLaSul
615321
asked Jan 3 at 9:57
LaSulLaSul
615321
615321
add a comment |
add a comment |
3 Answers
3
active
oldest
votes
Get the first record from the Row object using index 0 and get the value using the index "count"
from pyspark.sql.functions import col
data.groupby("card_bank", "failed").count().filter(col("failed") == "true").collect()[0]["count"]
answered Jan 3 at 10:10
Ernest S KirubakaranErnest S Kirubakaran
911510
1
Exactly what I was looking for :)
– LaSul
Jan 3 at 10:12
add a comment |
You need to get a row from the sequence (wither for loop or map function) and then row.getInt(2) according to https://spark.apache.org/docs/1.4.0/api/java/org/apache/spark/sql/Row.html.
answered Jan 3 at 10:05
windwind
360215
add a comment |
Try selecting the value from spark dataframe :-
df =data.groupBy("card_bank", "failed").count().filter(data["failed"] == "true").collect()
value = df.select("count").as[int].collect()
here, value will be a list.
answered Jan 3 at 10:07
SreejithSreejith
463
add a comment |
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3 Answers
3
active
oldest
votes
3 Answers
3
active
oldest
votes
active
oldest
votes
active
oldest
votes
Get the first record from the Row object using index 0 and get the value using the index "count"
from pyspark.sql.functions import col
data.groupby("card_bank", "failed").count().filter(col("failed") == "true").collect()[0]["count"]
answered Jan 3 at 10:10
Ernest S KirubakaranErnest S Kirubakaran
911510
1
Exactly what I was looking for :)
– LaSul
Jan 3 at 10:12
add a comment |
Get the first record from the Row object using index 0 and get the value using the index "count"
from pyspark.sql.functions import col
data.groupby("card_bank", "failed").count().filter(col("failed") == "true").collect()[0]["count"]
answered Jan 3 at 10:10
Ernest S KirubakaranErnest S Kirubakaran
911510
1
Exactly what I was looking for :)
– LaSul
Jan 3 at 10:12
add a comment |
Get the first record from the Row object using index 0 and get the value using the index "count"
from pyspark.sql.functions import col
data.groupby("card_bank", "failed").count().filter(col("failed") == "true").collect()[0]["count"]
answered Jan 3 at 10:10
Ernest S KirubakaranErnest S Kirubakaran
911510
Get the first record from the Row object using index 0 and get the value using the index "count"
from pyspark.sql.functions import col
data.groupby("card_bank", "failed").count().filter(col("failed") == "true").collect()[0]["count"]
answered Jan 3 at 10:10
Ernest S KirubakaranErnest S Kirubakaran
911510
answered Jan 3 at 10:10
Ernest S KirubakaranErnest S Kirubakaran
911510
answered Jan 3 at 10:10
Ernest S KirubakaranErnest S Kirubakaran
911510
answered Jan 3 at 10:10
Ernest S KirubakaranErnest S Kirubakaran
911510
911510
1
Exactly what I was looking for :)
– LaSul
Jan 3 at 10:12
add a comment |
1
Exactly what I was looking for :)
– LaSul
Jan 3 at 10:12
1
1
Exactly what I was looking for :)
– LaSul
Jan 3 at 10:12
Exactly what I was looking for :)
– LaSul
Jan 3 at 10:12
add a comment |
You need to get a row from the sequence (wither for loop or map function) and then row.getInt(2) according to https://spark.apache.org/docs/1.4.0/api/java/org/apache/spark/sql/Row.html.
answered Jan 3 at 10:05
windwind
360215
add a comment |
You need to get a row from the sequence (wither for loop or map function) and then row.getInt(2) according to https://spark.apache.org/docs/1.4.0/api/java/org/apache/spark/sql/Row.html.
answered Jan 3 at 10:05
windwind
360215
add a comment |
You need to get a row from the sequence (wither for loop or map function) and then row.getInt(2) according to https://spark.apache.org/docs/1.4.0/api/java/org/apache/spark/sql/Row.html.
answered Jan 3 at 10:05
windwind
360215
You need to get a row from the sequence (wither for loop or map function) and then row.getInt(2) according to https://spark.apache.org/docs/1.4.0/api/java/org/apache/spark/sql/Row.html.
answered Jan 3 at 10:05
windwind
360215
answered Jan 3 at 10:05
windwind
360215
answered Jan 3 at 10:05
windwind
360215
answered Jan 3 at 10:05
windwind
360215
360215
add a comment |
add a comment |
Try selecting the value from spark dataframe :-
df =data.groupBy("card_bank", "failed").count().filter(data["failed"] == "true").collect()
value = df.select("count").as[int].collect()
here, value will be a list.
answered Jan 3 at 10:07
SreejithSreejith
463
add a comment |
Try selecting the value from spark dataframe :-
df =data.groupBy("card_bank", "failed").count().filter(data["failed"] == "true").collect()
value = df.select("count").as[int].collect()
here, value will be a list.
answered Jan 3 at 10:07
SreejithSreejith
463
add a comment |
Try selecting the value from spark dataframe :-
df =data.groupBy("card_bank", "failed").count().filter(data["failed"] == "true").collect()
value = df.select("count").as[int].collect()
here, value will be a list.
answered Jan 3 at 10:07
SreejithSreejith
463
Try selecting the value from spark dataframe :-
df =data.groupBy("card_bank", "failed").count().filter(data["failed"] == "true").collect()
value = df.select("count").as[int].collect()
here, value will be a list.
answered Jan 3 at 10:07
SreejithSreejith
463
answered Jan 3 at 10:07
SreejithSreejith
463
answered Jan 3 at 10:07
SreejithSreejith
463
answered Jan 3 at 10:07
SreejithSreejith
463
463
add a comment |
add a comment |
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