How should I get the shape of a dask dataframe?

You can get the number of columns directly

len(df.columns) # this is fast 

You can also call len on the dataframe itself, though beware that this will trigger a computation.

len(df) # this requires a full scan of the data 

Dask.dataframe doesn't know how many records are in your data without first reading through all of it.

With shape you can do the following

a = df.shape a[0].compute(),a[1] 

This will show the shape just as it is shown with pandas

Well, I know this is a quite old question, but I had the same issue and I got an out-of-the-box solution which I just want to register here.

Considering your data, I'm wondering that it is originally saved in a CSV similar file; so, for my situation, I just count the lines of that file (minus one, the header line). Inspired by this answer here, this is the solution I'm using:

import dask.dataframe as dd from itertools import (takewhile,repeat) def rawincount(filename): f = open(filename, 'rb') bufgen = takewhile(lambda x: x, (f.raw.read(1024*1024) for _ in repeat(None))) return sum( buf.count(b'\n') for buf in bufgen ) filename = 'myHugeDataframe.csv' df = dd.read_csv(filename) df_shape = (rawincount(filename) - 1, len(df.columns)) print(f"Shape: {df_shape}") 

Hope this could help someone else as well.

print('(',len(df),',',len(df.columns),')') 

To get the shape we can try this way:

 dask_dataframe.describe().compute()  

"count" column of the index will give the number of rows

 len(dask_dataframe.columns) 

this will give the number of columns in the dataframe

For a dask dataframe named df:

df.compute().shape 

returns a tuple:
(number of rows, number of columns)

Getting number of columns by below code.

import dask.dataframe as dd dd1=dd.read_csv("filename.txt") print(dd1.info) #Output <class 'dask.dataframe.core.DataFrame'> Columns: 6 entries, CountryName to Value dtypes: object(4), float64(1), int64(1)