Pandas — Hierarchical Index & Cross-section
Open your Colab notebook and here are the follow-up exercises! — #PySeries#Episode 10
print(‘Hello, Advanced Pandas: Hierarchical Index & Cross-section!’)
Initializing a multi-level DataFrame:
import numpy as np
import pandas as pd
from numpy.random import randn
Pandas — MultiIndex & Advanced Index
As a convenience, we can pass a list of arrays directly into a special method below to construct a MultiIndex automatically:
hier_index=pd.MultiIndex.from_tuples(hier_index)df=pd.DataFrame(randn(6,2), hier_index, [‘A’, ‘B’])df
The reason that the MultiIndex matters is that it can allow you to do grouping, selection, and reshaping operations such as:
# If we want everything that is under ‘G1’, type df.loc():
# We will get a sub-set ‘G1’ of the DataFrame; check it out:df.loc[‘G1’]
We can continue to indexing off this, going deeper…
And deeper, and deeper…
The basic idea we can from the outside index continue calling inside deeper!
# Indexes do not have any namesdf.index.namesFrozenList([None, None])
But you can pass a list of names, for instance:
df.index.names = [‘Groups’, ‘Nums’]
# Now when we call it we have the outside label
# as ‘Groups’ and inside ‘Nums’df
Location and grabbing — Cross-Section:
Location and grab the group ‘G2’, nuns 2, ‘B’ column like this:
##Cross Section — Multi Level Index
# Let’s say we want to grab everything under ‘Nums’ = 1
# with both groups;
# What differentiates it from the loc method is that
# we can skip or go inside the multi-level index
# This is to say: grab a cross-section where the
# level is equal 1 and level is equal ‘Nums’df.xs(1, level=’Nums’)
print(“Thank you for Reading this Post! See you in the next PySeries Episode o/”)
Colab File link:)
00Episode#PySeries — Python — Jupiter Notebook Quick Start with VSCode — How to Set your Win10 Environment to use Jupiter Notebook
01Episode#PySeries — Python — Python 4 Engineers — Exercises! An overview of the Opportunities Offered by Python in Engineering!
02Episode#PySeries — Python — Geogebra Plus Linear Programming- We’ll Create a Geogebra program to help us with our linear programming
03Episode#PySeries — Python — Python 4 Engineers — More Exercises! — Another Round to Make Sure that Python is Really Amazing!
04Episode#PySeries — Python — Linear Regressions — The Basics — How to Understand Linear Regression Once and For All!
05Episode#PySeries — Python — NumPy Init & Python Review — A Crash Python Review & Initialization at NumPy lib.
06Episode#PySeries — Python — NumPy Arrays & Jupyter Notebook — Arithmetic Operations, Indexing & Slicing, and Conditional Selection w/ np arrays.
07Episode#PySeries — Python — Pandas — Intro & Series — What it is? How to use it?
08Episode#PySeries — Python — Pandas DataFrames — The primary Pandas data structure! It is a dict-like container for Series objects
09Episode#PySeries — Python — Python 4 Engineers — Even More Exercises! — More Practicing Coding Questions in Python!
10Episode#PySeries — Python — Pandas — Hierarchical Index & Cross-section — Open your Colab notebook and here are the follow-up exercises!
11Episode#PySeries — Python — Pandas — Missing Data — Let’s Continue the Python Exercises — Filling & Dropping Missing Data
12Episode#PySeries — Python — Pandas — Group By — Grouping large amounts of data and compute operations on these groups
13Episode#PySeries — Python — Pandas — Merging, Joining & Concatenations — Facilities For Easily Combining Together Series or DataFrame
14Episode#PySeries — Python — Pandas — Pandas Dataframe Examples: Column Operations
15Episode#PySeries — Python — Python 4 Engineers — Keeping It In The Short-Term Memory — Test Yourself! Coding in Python, Again!
16Episode#PySeries — NumPy — NumPy Review, Again;) — Python Review Free Exercises
17Episode#PySeries — Generators in Python — Python Review Free Hints
18Episode#PySeries — Pandas Review…Again;) — Python Review Free Exercise
19Episode#PySeries — MatlibPlot & Seaborn Python Libs — Reviewing theses Plotting & Statistics Packs
20Episode#PySeries — Seaborn Python Review — Reviewing theses Plotting & Statistics Packs