Pandas AttributeError: 'DataFrame' object has no attribute 'Datetime'

Question

I am working with holt winter method taking help from here. My data format is

 Year       Rate
0  2013  34.700000
1  2013  34.666667
2  2013  34.600000
3  2014  35.300000
4  2014  34.180000

Below is my code

import pandas as pd 

#Importing data

df = pd.read_csv('/home/rajnish.kumar/eclipse-workspace/ShivShakti/Result/weeklyDatarateyearonly/part-00000-971f46d7-a97d-4a7e-be41-dc840c2d0618-c000.csv')

df.Timestamp = pd.to_datetime(df.Datetime,format='%Y')

But I am getting this error:

AttributeError: 'DataFrame' object has no attribute 'Datetime'

Presumably you don't have a column called Datetime. This is why I prefer not to use the . accessor syntax for column names — roganjosh
– roganjosh, Commented Sep 5, 2018 at 10:04

desertnaut · Accepted Answer · 2018-09-05 11:59:16Z

5

If your data is indeed as shown (with columns Rate & Year), you are referencing a column (Datetime) that does not exist (in contrast with the data in the linked blog post, where there is indeed such a column):

import pandas as pd
data = {'Year':[2013, 2013, 2013, 2014, 2014], 'Rate':[34.7, 34.6,34.6,35.3,34.18]}
df = pd.DataFrame(data, columns=["Year", "Rate"])
df.Timestamp = pd.to_datetime(df.Datetime,format='%Y') 
# AttributeError: 'DataFrame' object has no attribute 'Datetime'

You should reference Year instead:

df['Timestamp'] = pd.to_datetime(df['Year'],format='%Y') 
df
# result:
   Year   Rate  Timestamp
0  2013  34.70 2013-01-01
1  2013  34.60 2013-01-01
2  2013  34.60 2013-01-01
3  2014  35.30 2014-01-01
4  2014  34.18 2014-01-01

edited Sep 5, 2018 at 11:59

answered Sep 5, 2018 at 11:07

desertnaut

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2 Comments

roganjosh Over a year ago

I'd still prefer df['Year'] over df.Year. There's just so many methods in Pandas for it to be confusing on the surface, let alone AttributeErrors on top

desertnaut Over a year ago

@roganjosh not a pandas expert, so I'll take your word (edited to df['Year']) ;)

Prasad Nadiger · Accepted Answer · 2021-02-18 10:14:30Z

0

You could use something like this:

import pandas as pd
data = {'Year':[2013, 2013, 2013, 2014, 2014], 'Rate':[34.7, 34.6,34.6,35.3,34.18]}
df = pd.DataFrame(data, columns=["Year", "Rate"])
df.Timestamp = pd.to_datetime(df.Year)

answered Feb 18, 2021 at 10:14

Prasad Nadiger

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