In [1]:

    

import pandas as pd


    

In [2]:

    

l_1d = [0, 1, 2]


    

In [3]:

    

s = pd.Series(l_1d)
print(s)


    

    




0    0
1    1
2    2
dtype: int64

In [4]:

    

s = pd.Series(l_1d, index=['row1', 'row2', 'row3'])
print(s)


    

    




row1    0
row2    1
row3    2
dtype: int64

In [5]:

    

l_2d = [[0, 1, 2], [3, 4, 5]]


    

In [6]:

    

df = pd.DataFrame(l_2d)
print(df)


    

    




   0  1  2
0  0  1  2
1  3  4  5

In [7]:

    

df = pd.DataFrame(l_2d,
                  index=['row1', 'row2'],
                  columns=['col1', 'col2', 'col3'])
print(df)


    

    




      col1  col2  col3
row1     0     1     2
row2     3     4     5

In [8]:

    

l_1d_index = [['Alice', 0], ['Bob', 1], ['Charlie', 2]]


    

In [9]:

    

index, value = zip(*l_1d_index)
print(index)


    

    




('Alice', 'Bob', 'Charlie')

In [10]:

    

print(value)


    

    




(0, 1, 2)

In [11]:

    

s_index = pd.Series(value, index=index)
print(s_index)


    

    




Alice      0
Bob        1
Charlie    2
dtype: int64

In [12]:

    

l_2d_index = [['Alice', 0, 0.0], ['Bob', 1, 0.1], ['Charlie', 2, 0.2]]


    

In [13]:

    

df_index = pd.DataFrame(l_2d_index, columns=['name', 'val1', 'val2'])
print(df_index)


    

    




      name  val1  val2
0    Alice     0   0.0
1      Bob     1   0.1
2  Charlie     2   0.2

In [14]:

    

df_index_set = df_index.set_index('name')
print(df_index_set)


    

    




         val1  val2
name               
Alice       0   0.0
Bob         1   0.1
Charlie     2   0.2

In [15]:

    

print(df_index_set.dtypes)


    

    




val1      int64
val2    float64
dtype: object

In [16]:

    

l_2d_index_columns = [['name', 'val1', 'val2'], ['Alice', 0, 0.0], ['Bob', 1, 0.1], ['Charlie', 2, 0.2]]


    

In [17]:

    

df_index_columns = pd.DataFrame(l_2d_index_columns[1:], columns=l_2d_index_columns[0])
print(df_index_columns)


    

    




      name  val1  val2
0    Alice     0   0.0
1      Bob     1   0.1
2  Charlie     2   0.2

In [18]:

    

df_index_columns_set = df_index_columns.set_index('name')
print(df_index_columns_set)


    

    




         val1  val2
name               
Alice       0   0.0
Bob         1   0.1
Charlie     2   0.2

In [19]:

    

s = pd.Series([0, 1, 2])
print(s)


    

    




0    0
1    1
2    2
dtype: int64

In [20]:

    

l_1d = s.values.tolist()
print(l_1d)


    

    




[0, 1, 2]

In [21]:

    

df = pd.DataFrame([[0, 1, 2], [3, 4, 5]])
print(df)


    

    




   0  1  2
0  0  1  2
1  3  4  5

In [22]:

    

l_2d = df.values.tolist()
print(l_2d)


    

    




[[0, 1, 2], [3, 4, 5]]

In [23]:

    

s_index = pd.Series([0, 1, 2], index=['row1', 'row2', 'row3'])
print(s_index)


    

    




row1    0
row2    1
row3    2
dtype: int64

In [24]:

    

l_1d = s_index.values.tolist()
print(l_1d)


    

    




[0, 1, 2]

In [25]:

    

df_index = pd.DataFrame([[0, 1, 2], [3, 4, 5]],
                        index=['row1', 'row2'],
                        columns=['col1', 'col2', 'col3'])
print(df_index)


    

    




      col1  col2  col3
row1     0     1     2
row2     3     4     5

In [26]:

    

l_2d = df_index.values.tolist()
print(l_2d)


    

    




[[0, 1, 2], [3, 4, 5]]

In [27]:

    

l_1d_index = s_index.reset_index().values.tolist()
print(l_1d_index)


    

    




[['row1', 0], ['row2', 1], ['row3', 2]]

In [28]:

    

l_2d_index = df_index.reset_index().values.tolist()
print(l_2d_index)


    

    




[['row1', 0, 1, 2], ['row2', 3, 4, 5]]

In [29]:

    

l_2d_index_columns = df_index.reset_index().T.reset_index().T.values.tolist()
print(l_2d_index_columns)


    

    




[['index', 'col1', 'col2', 'col3'], ['row1', 0, 1, 2], ['row2', 3, 4, 5]]

In [30]:

    

print(s_index)


    

    




row1    0
row2    1
row3    2
dtype: int64

In [31]:

    

print(s_index.index)


    

    




Index(['row1', 'row2', 'row3'], dtype='object')

In [32]:

    

print(type(s_index.index))


    

    




<class 'pandas.core.indexes.base.Index'>

In [33]:

    

print(s_index.index.tolist())


    

    




['row1', 'row2', 'row3']

In [34]:

    

print(type(s_index.index.tolist()))


    

    




<class 'list'>

In [35]:

    

for i in s_index.index:
    print(i, type(i))


    

    




row1 <class 'str'>
row2 <class 'str'>
row3 <class 'str'>

In [36]:

    

print(s_index.index[0])


    

    




row1

In [37]:

    

print(s_index.index[:2])


    

    




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

In [38]:

    

# s_index.index[0] = 'ROW1'
# TypeError: Index does not support mutable operations


    

In [39]:

    

print(df_index)


    

    




      col1  col2  col3
row1     0     1     2
row2     3     4     5

In [40]:

    

print(df_index.index)


    

    




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

In [41]:

    

print(df_index.index.tolist())


    

    




['row1', 'row2']

In [42]:

    

print(df_index.columns)


    

    




Index(['col1', 'col2', 'col3'], dtype='object')

In [43]:

    

print(df_index.columns.tolist())


    

    




['col1', 'col2', 'col3']