CODEWITHSUNDEEP
pythonpandasextenddatetimeindex
mk_sch
mk_sch

Reputation: 1070

Extending Timeindex by adding new values in another column in Pandas.

Assume that I have the following dataframe in Pandas:

index = pd.date_range(start=pd.Timestamp('2017-07-01'), end=pd.Timestamp('2017-07-01') + pd.Timedelta('10D'))
df = pd.DataFrame(data=np.random.rand(11), index=index , columns=['rand'])
df.head()

              rand
2017-07-01 0.794164
2017-07-02 0.948194
2017-07-03 0.432187
2017-07-04 0.750968
2017-07-05 0.591830

I want to add ten new values to rand column by extending index column by the number of added values i.e. until 2017-07-19. I wonder if there is any way that the time index can be extended automatically only by adding values to rand column.

Upvotes: 2

Views: 1618

Answers (2)

jezrael
jezrael

Reputation: 862406

You can create new DataFrame and then concat or append:

a = pd.date_range(df.index[-1] + pd.offsets.DateOffset(1), '2017-07-19')
df1 = pd.DataFrame(data=np.random.rand(8), index=a , columns=['rand'])

df = pd.concat([df, df1])
#alternative solution
#df = df.append(df1)
print (df)
                rand
2017-07-01  0.989012
2017-07-02  0.549545
2017-07-03  0.281447
2017-07-04  0.077290
2017-07-05  0.444469
2017-07-06  0.472808
2017-07-07  0.048522
2017-07-08  0.163324
2017-07-09  0.115951
2017-07-10  0.627392
2017-07-11  0.856182
2017-07-12  0.650102
2017-07-13  0.990722
2017-07-14  0.470351
2017-07-15  0.618294
2017-07-16  0.282667
2017-07-17  0.976003
2017-07-18  0.673068
2017-07-19  0.440531

Upvotes: 1

Bharath M Shetty
Bharath M Shetty

Reputation: 30605

You can first create the dataframe and then set the index by setting period to the length of the dataframe and frequency to 1D. If you want to add new 'rand' data, you can use pd.concat then set the index i.e 

df = pd.DataFrame(data=np.random.rand(25), columns=['rand'])
index = pd.date_range(start=pd.Timestamp('2017-07-01'),freq='1D',periods=df.shape[0])
df.set_index(index)

Output : 

                rand
2017-07-01  0.128300
2017-07-02  0.039629
2017-07-03  0.797066
2017-07-04  0.023662
2017-07-05  0.350117
2017-07-06  0.945745
2017-07-07  0.182427
2017-07-08  0.792960
2017-07-09  0.066210
2017-07-10  0.774758
2017-07-11  0.824564
2017-07-12  0.872008
2017-07-13  0.996188
2017-07-14  0.671798
2017-07-15  0.204903
2017-07-16  0.087394
2017-07-17  0.718709
2017-07-18  0.224255
2017-07-19  0.576668
2017-07-20  0.789603
2017-07-21  0.352212
2017-07-22  0.601235
2017-07-23  0.984145
2017-07-24  0.182860
2017-07-25  0.796244

Upvotes: 1

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