(Python Example for Beginners)
Write a Pandas program to create a time series object that has time indexed data. Also select the dates of same year and select the dates between certain dates.
Python Code :
import pandas as pd index = pd.DatetimeIndex(['2011-09-02', '2012-08-04', '2015-09-03', '2010-08-04', '2015-03-03', '2011-08-04', '2015-04-03', '2012-08-04']) s_dates = pd.Series([0, 1, 2, 3, 4, 5, 6, 7], index=index) print("Time series object with indexed data:") print(s_dates) print("nDates of same year:") print(s_dates['2015']) print("nDates between 2012-01-01 and 2012-12-31") print(s_dates['2012-01-01':'2012-12-31'])
Time series object with indexed data: 2011-09-02 0 2012-08-04 1 2015-09-03 2 2010-08-04 3 2015-03-03 4 2011-08-04 5 2015-04-03 6 2012-08-04 7 dtype: int64 Dates of same year: 2015-09-03 2 2015-03-03 4 2015-04-03 6 dtype: int64 Dates between 2012-01-01 and 2012-12-31 2012-08-04 1 2012-08-04 7 dtype: int64
Python Example for Beginners
Two Machine Learning Fields
There are two sides to machine learning:
- Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
- Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
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