In [1]:

    

import pandas as pd


    

In [2]:

    

df = pd.DataFrame({'list': [[0, 0], [0, 1], [1, 0], [1, 1]]},
                  index=pd.date_range('2018-01-01', '2018-01-04', freq='D'))


    

In [3]:

    

print(df)


    

    




              list
2018-01-01  [0, 0]
2018-01-02  [0, 1]
2018-01-03  [1, 0]
2018-01-04  [1, 1]

In [4]:

    

print(df.index)


    

    




DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04'], dtype='datetime64[ns]', freq='D')

In [5]:

    

print(type(df['list'][0]))


    

    




<class 'list'>

In [6]:

    

df.to_csv('data/dst/pandas_obj.csv')


    

In [7]:

    

df_from_csv = pd.read_csv('data/dst/pandas_obj.csv', index_col=0, parse_dates=True)


    

In [8]:

    

print(df_from_csv)


    

    




              list
2018-01-01  [0, 0]
2018-01-02  [0, 1]
2018-01-03  [1, 0]
2018-01-04  [1, 1]

In [9]:

    

print(df_from_csv.index)


    

    




DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04'], dtype='datetime64[ns]', freq=None)

In [10]:

    

print(type(df_from_csv['list'][0]))


    

    




<class 'str'>

In [11]:

    

df_from_csv['list'] = df_from_csv['list'].apply(eval)


    

In [12]:

    

print(df_from_csv)


    

    




              list
2018-01-01  [0, 0]
2018-01-02  [0, 1]
2018-01-03  [1, 0]
2018-01-04  [1, 1]

In [13]:

    

print(type(df_from_csv['list'][0]))


    

    




<class 'list'>

In [14]:

    

df.to_pickle('data/dst/pandas_obj.pkl')


    

In [15]:

    

df_from_pkl = pd.read_pickle('data/dst/pandas_obj.pkl')


    

In [16]:

    

print(df_from_pkl)


    

    




              list
2018-01-01  [0, 0]
2018-01-02  [0, 1]
2018-01-03  [1, 0]
2018-01-04  [1, 1]

In [17]:

    

print(df_from_pkl.index)


    

    




DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04'], dtype='datetime64[ns]', freq='D')

In [18]:

    

print(type(df_from_pkl['list'][0]))


    

    




<class 'list'>

In [19]:

    

df.to_pickle('data/dst/pandas_obj.zip')


    

In [20]:

    

df_from_pkl_zip = pd.read_pickle('data/dst/pandas_obj.zip')


    

In [21]:

    

print(df_from_pkl_zip)


    

    




              list
2018-01-01  [0, 0]
2018-01-02  [0, 1]
2018-01-03  [1, 0]
2018-01-04  [1, 1]