In [1]:

    

import pandas as pd


    

In [2]:

    

df = pd.DataFrame(pd.np.arange(12).reshape(3, 4), columns=['a', 'b', 'c', 'd'], index=['x', 'y', 'z'])
print(df)


    

    




   a  b   c   d
x  0  1   2   3
y  4  5   6   7
z  8  9  10  11

In [3]:

    

print((df > 3) & (df % 2 == 0))


    

    




       a      b      c      d
x  False  False  False  False
y   True  False   True  False
z   True  False   True  False

In [4]:

    

# print((df > 3) and (df % 2 == 0))
# ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().


    

In [5]:

    

# print(df > 3 & df % 2 == 0)
# ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().


    

In [6]:

    

print(df & 7)


    

    




   a  b  c  d
x  0  1  2  3
y  4  5  6  7
z  0  1  2  3

In [7]:

    

print(df | 1)


    

    




   a  b   c   d
x  1  1   3   3
y  5  5   7   7
z  9  9  11  11

In [8]:

    

# print(df << 1)
# TypeError: unsupported operand type(s) for <<: 'DataFrame' and 'int'


    

In [9]:

    

# print(df << df)
# TypeError: unsupported operand type(s) for <<: 'DataFrame' and 'DataFrame'


    

In [10]:

    

print(df > 3)


    

    




       a      b      c      d
x  False  False  False  False
y   True   True   True   True
z   True   True   True   True

In [11]:

    

print((df > 3).all())


    

    




a    False
b    False
c    False
d    False
dtype: bool

In [12]:

    

print((df > 3).all(axis=1))


    

    




x    False
y     True
z     True
dtype: bool

In [13]:

    

print((df > 3).all(axis=None))


    

    




False

In [14]:

    

print(df.empty)


    

    




False

In [15]:

    

df_empty = pd.DataFrame()
print(df_empty.empty)


    

    




True

In [16]:

    

print(df.size)


    

    




12

In [17]:

    

print(df_empty.size)


    

    




0