In [1]:

    

import pandas as pd
import pprint
from collections import OrderedDict


    

In [2]:

    

df = pd.DataFrame({'col1': [1, 2, 3], 'col2': ['a', 'x', 'あ']},
                  index=['row1', 'row2', 'row3'])


    

In [3]:

    

print(df)


    

    




      col1 col2
row1     1    a
row2     2    x
row3     3    あ

In [4]:

    

d = df.to_dict()


    

In [5]:

    

pprint.pprint(d)


    

    




{'col1': {'row1': 1, 'row2': 2, 'row3': 3},
 'col2': {'row1': 'a', 'row2': 'x', 'row3': 'あ'}}

In [6]:

    

print(type(d))


    

    




<class 'dict'>

In [7]:

    

d_dict = df.to_dict(orient='dict')


    

In [8]:

    

pprint.pprint(d_dict)


    

    




{'col1': {'row1': 1, 'row2': 2, 'row3': 3},
 'col2': {'row1': 'a', 'row2': 'x', 'row3': 'あ'}}

In [9]:

    

print(d_dict['col1'])


    

    




{'row1': 1, 'row2': 2, 'row3': 3}

In [10]:

    

print(type(d_dict['col1']))


    

    




<class 'dict'>

In [11]:

    

d_list = df.to_dict(orient='list')


    

In [12]:

    

pprint.pprint(d_list)


    

    




{'col1': [1, 2, 3], 'col2': ['a', 'x', 'あ']}

In [13]:

    

print(d_list['col1'])


    

    




[1, 2, 3]

In [14]:

    

print(type(d_list['col1']))


    

    




<class 'list'>

In [15]:

    

d_series = df.to_dict(orient='series')


    

In [16]:

    

pprint.pprint(d_series)


    

    




{'col1': row1    1
row2    2
row3    3
Name: col1, dtype: int64,
 'col2': row1    a
row2    x
row3    あ
Name: col2, dtype: object}

In [17]:

    

print(d_series['col1'])


    

    




row1    1
row2    2
row3    3
Name: col1, dtype: int64

In [18]:

    

print(type(d_series['col1']))


    

    




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

In [19]:

    

d_split = df.to_dict(orient='split')


    

In [20]:

    

pprint.pprint(d_split)


    

    




{'columns': ['col1', 'col2'],
 'data': [[1, 'a'], [2, 'x'], [3, 'あ']],
 'index': ['row1', 'row2', 'row3']}

In [21]:

    

print(d_split['columns'])


    

    




['col1', 'col2']

In [22]:

    

print(type(d_split['columns']))


    

    




<class 'list'>

In [23]:

    

l_records = df.to_dict(orient='records')


    

In [24]:

    

pprint.pprint(l_records)


    

    




[{'col1': 1, 'col2': 'a'}, {'col1': 2, 'col2': 'x'}, {'col1': 3, 'col2': 'あ'}]

In [25]:

    

print(type(l_records))


    

    




<class 'list'>

In [26]:

    

print(l_records[0])


    

    




{'col1': 1, 'col2': 'a'}

In [27]:

    

print(type(l_records[0]))


    

    




<class 'dict'>

In [28]:

    

d_index = df.to_dict(orient='index')


    

In [29]:

    

pprint.pprint(d_index)


    

    




{'row1': {'col1': 1, 'col2': 'a'},
 'row2': {'col1': 2, 'col2': 'x'},
 'row3': {'col1': 3, 'col2': 'あ'}}

In [30]:

    

print(d_index['row1'])


    

    




{'col1': 1, 'col2': 'a'}

In [31]:

    

print(type(d_index['row1']))


    

    




<class 'dict'>

In [32]:

    

od = df.to_dict(into=OrderedDict)


    

In [33]:

    

pprint.pprint(od)


    

    




OrderedDict([('col1', OrderedDict([('row1', 1), ('row2', 2), ('row3', 3)])),
             ('col2',
              OrderedDict([('row1', 'a'), ('row2', 'x'), ('row3', 'あ')]))])

In [34]:

    

print(type(od))


    

    




<class 'collections.OrderedDict'>

In [35]:

    

print(od['col1'])


    

    




OrderedDict([('row1', 1), ('row2', 2), ('row3', 3)])

In [36]:

    

print(type(od['col1']))


    

    




<class 'collections.OrderedDict'>

In [37]:

    

print(df.index)


    

    




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

In [38]:

    

print(df['col1'])


    

    




row1    1
row2    2
row3    3
Name: col1, dtype: int64

In [39]:

    

d_col = dict(zip(df.index, df['col1']))


    

In [40]:

    

print(d_col)


    

    




{'row1': 1, 'row2': 2, 'row3': 3}

In [41]:

    

d_row = dict(zip(df.columns, df.loc['row1']))


    

In [42]:

    

print(d_row)


    

    




{'col1': 1, 'col2': 'a'}