Get into an interactive Python session with numpy and pandas, and experiment

Make a dataframe:

In [394]: df=pd.DataFrame(np.eye(3))                                            
In [395]: df                                                                    
Out[395]: 
     0    1    2
0  1.0  0.0  0.0
1  0.0  1.0  0.0
2  0.0  0.0  1.0

Check its shape. That's a tuple (basic Python object):

In [396]: df.shape                                                              
Out[396]: (3, 3)
In [397]: df.shape[0]     # first element of the tuple                                                          
Out[397]: 3

Repeat with the shape parameter is just like using the number 3:

In [398]: np.repeat('red', df.shape[0])                                         
Out[398]: array(['red', 'red', 'red'], dtype='<U3')

Pandas and numpy are running in Python. So the regular evaluation order of Python applies.

pd.shape will give you the number of rows and columns present in the dataFrame.

where, df.shape[0] will give you the total rows present in the dataFrame.

and, df.shape[1] will give you the number of columns present in the dataFrame.

Example:

df = pd.DataFrame({'Date':['10/2/2011', '11/2/2011', '12/2/2011'], 
                    'Phrases':['I have a cool family', 'I like avocados', 'I would like to go to school']})


df
Out[26]: 
        Date                       Phrases
0  10/2/2011          I have a cool family
1  11/2/2011               I like avocados
2  12/2/2011  I would like to go to school

df.shape
Out[27]: (3, 2)

df.shape[0]   #number of rows
Out[28]: 3

df.shape[1]   #number of columns
Out[29]: 2