Pandas: transform a dbf Table into a dataframe

Question

I want to read a dbf file of an ArcGIS shapefile and dump it into a pandas dataframe. I am currently using the dbf package.

I have apparently b

Answer 1

Performance can be an issue. I tested a few of the libraries suggested above and elsewhere. For my test, I used a small dbf file of 17 columns and 23 records (7 kb).

Package simpledbf has a straightforward method to_dataframe(). And the practical aspect of the DBF table object of dbfread is the possibility to just iterate over it by adding it as an argument to Python's builtin function iter(), of which the result can be used to directly initialise a dataframe. In the case of pysal, I used the function dbf2DF as decribed here. The data from the other libraries I added to the dataframe by using the method shown above. However, only after retrieving the field names so that I could initialise the dataframe with the right column names first: from the fieldNames, _meta.keys and by means of the function ListFields respectively.

Probably adding records 1 by 1 is not the fastest way to obtain a filled dataframe, meaning that tests with dbfpy, dbf and arcpy would result in more favourable figures when a smarter way would be chosen to add the data to the dataframe. All the same, I hope the following table - with times in seconds - is useful:

simpledbf   0.0030
dbfread     0.0060
dbfpy       0.0140
pysal       0.0160
dbf         0.0210
arcpy       2.7770