When I call resource.to_pandas() on a resource that has a primaryKey defined that key is used as an index for the dataframe. This is a reasonable default behavior, but took me some time to realize/debug.
Possible Solutions
- Add an option for the
to_pandas function of index=false, (with a default of true) which follows a similar pattern to pandas to_csv function.
- Add additional documentation on the to_pandas function. The only thing I could find online for this was here: https://framework.frictionlessdata.io/docs/formats/pandas.html
Adding additional documentation here that describes how primaryKey fields are used to index the dataframe would've cleared this up for me.
Current Workaround
Now that I know that to_pandas works this way I can call df.reset_index() [docs] to turn those index columns into regular columns, which is what I want in my situation.
When I call
resource.to_pandas()on a resource that has a primaryKey defined that key is used as an index for the dataframe. This is a reasonable default behavior, but took me some time to realize/debug.Possible Solutions
to_pandasfunction ofindex=false, (with a default of true) which follows a similar pattern to pandas to_csv function.Adding additional documentation here that describes how primaryKey fields are used to index the dataframe would've cleared this up for me.
Current Workaround
Now that I know that
to_pandasworks this way I can calldf.reset_index()[docs] to turn those index columns into regular columns, which is what I want in my situation.