(Python Example for Beginners)
Write a Pandas program to drop a index level from a multi-level column index of a dataframe.
Note: Levels are 0-indexed beginning from the top.
Python Code :
import pandas as pd cols = pd.MultiIndex.from_tuples([("a", "x"), ("a", "y"), ("a", "z")]) print("nConstruct a Dataframe using the said MultiIndex levels: ") df = pd.DataFrame([[1,2,3], [3,4,5], [5,6,7]], columns=cols) print(df) print("nRemove the top level index:") df.columns = df.columns.droplevel(0) print(df) df = pd.DataFrame([[1,2,3], [3,4,5], [5,6,7]], columns=cols) print("nOriginal dataframe:") print(df) print("nRemove the index next to top level:") df.columns = df.columns.droplevel(1) print(df)
Construct a Dataframe using the said MultiIndex levels: a x y z 0 1 2 3 1 3 4 5 2 5 6 7 Remove the top level index: x y z 0 1 2 3 1 3 4 5 2 5 6 7 Original dataframe: a x y z 0 1 2 3 1 3 4 5 2 5 6 7 Remove the index next to top level: a a a 0 1 2 3 1 3 4 5 2 5 6 7
Pandas Example – Write a Pandas program to drop a index level from a multi-level column index of a dataframe
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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