Load csv file as a dataframe?

[Kaniz_Fatma]

spark-csv is part of core Spark functionality and doesn't require a separate library.

df = spark.read.format("csv").option("header", "true").load("file.csv")

[Kaniz_Fatma]

In scala,(this works for any format-in delimiter mention "," for csv, "\t" for tsv etc)

val df = sqlContext.read.format("com.databricks.spark.csv")

.option("delimiter", ",")

.load("csvfile.csv")

[Hubert-Dudek]

as @Kaniz Fatma​ wrote you can use native functions for it:

df = spark.read.format("csv").option("header", "true").load("file.csv")

Alternative really nice way is to use sql syntax for that:

%sql
CREATE TEMPORARY VIEW diamonds
USING CSV
OPTIONS (path "/databricks-datasets/Rdatasets/data-001/csv/ggplot2/diamonds.csv", header "true", mode "FAILFAST")

Here is spark documentation:

https://spark.apache.org/docs/latest/api/python/reference/api/pyspark.sql.DataFrameReader.csv.html?h...

and databricks documentation:

https://docs.databricks.com/data/data-sources/read-csv.html