azureml_dataprep_rslex_csv_to_pandas_dataframe.py

1import azureml.dataprep as dprep
2
3# The rslex engine is automatically utilized by azureml-dataprep 
4# when the azureml-dataprep-rslex package is installed in the environment.
5
6# 1. Create a dataflow to read a CSV file
7# Replace 'path/to/your/data.csv' with your actual file path or datastore URI
8dataflow = dprep.read_csv(path='path/to/your/data.csv')
9
10# 2. Preview the first 10 rows
11# This triggers the rslex engine to process and return the data
12print(dataflow.head(10))
13
14# 3. Convert the dataflow to a Pandas DataFrame for further analysis
15df = dataflow.to_pandas_dataframe()
16
17print(df.info())