Python and R can be used together for data manipulation in Databricks Notebook by leveraging the functionality of the databricks-connect library. Here are the steps to follow:
First, install the databricks-connect library on your local machine using the command: pip install databricks-connect
Next, setup databricks-connect by running the command: databricks-connect configure
. This will prompt you to enter your Databricks URL and Personal Access Token.
Once you have set up databricks-connect, you can connect to your Databricks workspace by running the command: databricks-connect test
Now, you can use both Python and R in the same Databricks Notebook by specifying the language at the beginning of each cell using the %python
or %r
magic commands. For example:
%python
df = spark.read.csv("path/to/file")
%r
library(dplyr)
df <- df %>% select(col1, col2)
Note that you can use spark_read_csv()
function from sparklyr package if you want to read .csv
files using R.
You can also pass data between Python and R by using the py
and r
variables. For example:
%python
py_var = "Hello from Python!"
%r
r_var <- paste(r_var, py$py_var)
print(r_var)
Note that py$
is used to access the Python variable py_var
.
Finally, you can also install R packages on your Databricks workspace by running the command: install.packages("package_name")
within an R cell in the Databricks Notebook.
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Asked: 2021-04-09 11:00:00 +0000
Seen: 11 times
Last updated: Jun 13 '22
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