In [1]:

    

import pandas as pd


    

In [2]:

    

df = pd.DataFrame({'col0': [0, 1, 2], 'col1': [0.0, 0.1, 0.2], 'col2': ['a', 'b', 'c']},
                  index=['row0', 'row1', 'row2'])
print(df)


    

    




      col0  col1 col2
row0     0   0.0    a
row1     1   0.1    b
row2     2   0.2    c

In [3]:

    

print(df.dtypes)


    

    




col0      int64
col1    float64
col2     object
dtype: object

In [4]:

    

s = df['col1']
print(s)


    

    




row0    0.0
row1    0.1
row2    0.2
Name: col1, dtype: float64

In [5]:

    

print(type(s))


    

    




<class 'pandas.core.series.Series'>

In [6]:

    

print(s.dtype)


    

    




float64

In [7]:

    

print(s.index)


    

    




Index(['row0', 'row1', 'row2'], dtype='object')

In [8]:

    

print(s.name)


    

    




col1

In [9]:

    

print(df.loc[:, 'col1'])


    

    




row0    0.0
row1    0.1
row2    0.2
Name: col1, dtype: float64

In [10]:

    

print(df.iloc[:, 2])


    

    




row0    a
row1    b
row2    c
Name: col2, dtype: object

In [11]:

    

print(df.iloc[[0, 2], 2])


    

    




row0    a
row2    c
Name: col2, dtype: object

In [12]:

    

print(df.iloc[:2, 2])


    

    




row0    a
row1    b
Name: col2, dtype: object

In [13]:

    

df_only = df[['col1']]
print(df_only)


    

    




      col1
row0   0.0
row1   0.1
row2   0.2

In [14]:

    

print(type(df_only))


    

    




<class 'pandas.core.frame.DataFrame'>

In [15]:

    

df_only2 = df.iloc[:, 1:2]
print(df_only2)


    

    




      col1
row0   0.0
row1   0.1
row2   0.2

In [16]:

    

print(type(df_only2))


    

    




<class 'pandas.core.frame.DataFrame'>

In [17]:

    

s_r = df.loc['row1', :]
print(s_r)


    

    




col0      1
col1    0.1
col2      b
Name: row1, dtype: object

In [18]:

    

print(type(s_r))


    

    




<class 'pandas.core.series.Series'>

In [19]:

    

print(s_r.dtype)


    

    




object

In [20]:

    

print(s_r.index)


    

    




Index(['col0', 'col1', 'col2'], dtype='object')

In [21]:

    

print(s_r.name)


    

    




row1

In [22]:

    

print(df.loc['row1'])


    

    




col0      1
col1    0.1
col2      b
Name: row1, dtype: object

In [23]:

    

print(df.iloc[2, [0, 2]])


    

    




col0    2
col2    c
Name: row2, dtype: object

In [24]:

    

df_only_r = df.iloc[[1]]
print(df_only_r)


    

    




      col0  col1 col2
row1     1   0.1    b

In [25]:

    

print(type(df_only_r))


    

    




<class 'pandas.core.frame.DataFrame'>

In [26]:

    

df_only_r2 = df[1:2]
print(df_only_r2)


    

    




      col0  col1 col2
row1     1   0.1    b

In [27]:

    

print(type(df_only_r2))


    

    




<class 'pandas.core.frame.DataFrame'>

In [28]:

    

print(s_r[0])


    

    




1

In [29]:

    

print(type(s_r[0]))


    

    




<class 'numpy.int64'>

In [30]:

    

print(s_r[1])


    

    




0.1

In [31]:

    

print(type(s_r[1]))


    

    




<class 'numpy.float64'>

In [32]:

    

print(s_r[2])


    

    




b

In [33]:

    

print(type(s_r[2]))


    

    




<class 'str'>

In [34]:

    

df_n = df[['col0', 'col1']]
print(df_n)


    

    




      col0  col1
row0     0   0.0
row1     1   0.1
row2     2   0.2

In [35]:

    

print(df_n.dtypes)


    

    




col0      int64
col1    float64
dtype: object

In [36]:

    

s_n_r = df_n.iloc[1]
print(s_n_r)


    

    




col0    1.0
col1    0.1
Name: row1, dtype: float64

In [37]:

    

print(s_n_r[0])


    

    




1.0

In [38]:

    

print(type(s_n_r[0]))


    

    




<class 'numpy.float64'>

In [39]:

    

print(s_n_r[1])


    

    




0.1

In [40]:

    

print(type(s_n_r[1]))


    

    




<class 'numpy.float64'>

In [41]:

    

print(df)


    

    




      col0  col1 col2
row0     0   0.0    a
row1     1   0.1    b
row2     2   0.2    c

In [42]:

    

s = df['col0']
print(s)


    

    




row0    0
row1    1
row2    2
Name: col0, dtype: int64

In [43]:

    

df.iat[0, 0] = 100
print(df)


    

    




      col0  col1 col2
row0   100   0.0    a
row1     1   0.1    b
row2     2   0.2    c

In [44]:

    

print(s)


    

    




row0    100
row1      1
row2      2
Name: col0, dtype: int64

In [45]:

    

s_copy = df['col1'].copy()
print(s_copy)


    

    




row0    0.0
row1    0.1
row2    0.2
Name: col1, dtype: float64

In [46]:

    

df.iat[0, 1] = 100
print(df)


    

    




      col0   col1 col2
row0   100  100.0    a
row1     1    0.1    b
row2     2    0.2    c

In [47]:

    

print(s_copy)


    

    




row0    0.0
row1    0.1
row2    0.2
Name: col1, dtype: float64

In [48]:

    

s_l = df.loc[['row0', 'row2'], 'col2']
print(s_l)


    

    




row0    a
row2    c
Name: col2, dtype: object

In [49]:

    

df.iat[0, 2] = 'XXX'
print(df)


    

    




      col0   col1 col2
row0   100  100.0  XXX
row1     1    0.1    b
row2     2    0.2    c

In [50]:

    

print(s_l)


    

    




row0    a
row2    c
Name: col2, dtype: object