i am trying to read csv file using databricks, i am getting error like ......FileNotFoundError: [Errno 2] No such file or directory: '/dbfs/FileStore/tables/world_bank.csv'

[Venky]

i am trying to read csv file using databricks, i am getting error like ......FileNotFoundError: [Errno 2] No such file or directory: '/dbfs/FileStore/tables/world_bank.csv'

[Hubert-Dudek]

I see that you are using databricks-course-cluster which have probably some limited functionality. Not sure where dbfs is mounted there. When you are using dbutils it display path for dbfs mount (dbfs file system).

Please use spark code instead of pandas so it will be executed properly:

df = spark.read.csv('dbfs:/FileStore/tables/world_bank.csv')
display(df)

[Alexis]

ops I didn't see the other answers, anyway here you have how to use %fs magic to do the same that dbutils.fs.ls() utils.

Just before to create the spark data frame, check if the file exists in the mentioned path.

You can use the %fs magic like this:

[klllmmm]

Pls help,

I have the same problem

[-werners-]

I see you use pandas to read from dbfs.

But pandas will only read from local files,

see this topic also. It is about databricks-connect but the same principles apply.

So what you should do is first read the file using spark.read.csv and then converting the spark df to a pandas df.

[Eagle78]

I had the same issue: geopandas in Databricks notebooks does not open shapefiles from an Azure Storage mount.
I managed to copy the shapefile to the Databricks workspace using 

dbutils.fs.cp(shapefile_path, f"file:{local_shapefile_copy_dest_path}") 

The 'file:' prefix proved to be crucial here.

and then: 

gdf = gpd.read_file(shapefile_path.replace('dbfs:', ''))
gdf.display()

I copy the results back to the dbfs mount using

dbutils.fs.cp(f"file:{geoparquet_path}", f"{raw_path}{geoparquet_file_basename}.parquet")

---

@-werners- wrote:

I see you use pandas to read from dbfs.

But pandas will only read from local files,

see this topic also. It is about databricks-connect but the same principles apply.

So what you should do is first read the file using spark.read.csv and then converting the spark df to a pandas df.

---

---

@-werners- wrote:

I see you use pandas to read from dbfs.

But pandas will only read from local files,

see this topic also. It is about databricks-connect but the same principles apply.

So what you should do is first read the file using spark.read.csv and then converting the spark df to a pandas df.

---

[Eagle78]

Ik convert to parquet using

gdf.to_parquet(f"/dbfs{raw_path}/{file_name}.parquet") 

[Alexis · Accepted solution]

Hi

you can try:

my_df = spark.read.format("csv")

      .option("inferSchema","true")  # to get the types from your data

      .option("sep",",")            # if your file is using "," as separator

      .option("header","true")       # if your file have the header in the first row

      .load("/FileStore/tables/CREDIT_1.CSV")

display(my_df)

from above you can see that my_df is a spark dataframe and from there you can start with you code.