# Single CSV

In this example, we'll use a CSV file of Netflix movies.

from zef import *from zef.ops import *g = Graph()file_path = "something/my_file.csv"                                     # this is where your CSV file is locateddf = file_path | load_file | run | get['content']  | collect            # the loaded file is now a pandas dataframe object

## Mapping rows and columns into graph entities​

Each row should represent a specific entity. In this example, each row will be represented as an ET.Movie. Column names will be imported over as is by default.

mapping = {"row": "Movie"}

You also have the option of renaming the column names upon import.

mapping = {"row": "Movie", "columns": {"ratingLevel": "RatingDescription", "ratingDescription": "RatingScore"}}

Here, the columns "ratingLevel" and "ratingDescription" will be renamed while the other column names will remain as is.

## Importing pandas dataframe object into a Zef graph​

Passing our dataframe with mapping into "pandas_to_gd" produces a GraphDelta with the required transformations that can be applied to any Zef graph (in this instance, a new graph g).

pandas_to_gd(df, mapping) | g | run

Note that when you run the above command, it may take a few seconds (depending on the size of the CSV).

## Explore the graph​

You can now take a quick look at the graph and begin exploring!

yo(g)