Pandas 101: Data Manipulation in Python

Pandas 101: Data Manipulation in Python

Pandas is the most popular Python library for data manipulation and analysis. It provides high-performance, easy-to-use data structures and data analysis tools. …

From Pandas to Polars: A Paradigm Shift in DataFrame Processing

From Pandas to Polars: A Paradigm Shift in DataFrame Processing

Welcome to the first installment of our Polars blog series! If you’ve spent years mastering Pandas and are curious about what …

Subsetting a DataFrame in Pandas

Subsetting a DataFrame in Pandas

Master the art of data filtering with practical examples using the Iris dataset. Learn different techniques to filter and subset pandas DataFrames efficiently for …

Mastering Polars Data Types and Missing Values

Mastering Polars Data Types and Missing Values

Polars is a lightning-fast DataFrame library for Rust and Python. One of its strengths lies in its strict and expressive type system. Understanding …

Advanced Polars Expressions: String Operations & Complex Data Types

Advanced Polars Expressions: String Operations & Complex Data Types

Welcome to the second installment of our Polars mastery series! Building on the foundational concepts from Part 1, we’ll …

From Pandas to Polars: A Paradigm Shift in DataFrame Processing

Welcome to the first installment of our Polars blog series! If you’ve spent years mastering Pandas and are curious about what makes Polars the talk of the data community, this post is your …

Advanced Pandas GroupBy and Window Functions for Data Engineering and Analytics

Session Outline: Advanced GroupBy and Window Functions in Pandas

1. Introduction to GroupBy and Its Role in Data Engineering (5 minutes)

• Overview: Recap of GroupBy as a split-apply-combine paradigm, …

Part 5 - Plotting Using Seaborn - Radar

Introduction and Data preparation

Please follow the folloing links regarding data preparation and previous posts to follow along -

• For Data Preparation - Part 0 - Plotting Using Seaborn - Data …

Part 2 - Plotting Using Seaborn - Distribution Plot, Facet Grid

Introduction and Data preparation

Please follow the folloing links regarding data preparation and previous posts to follow along -

• For Data Preparation - Part 0 - Plotting Using Seaborn - Data …

Part 3 - Plotting Using Seaborn - Donut

Introduction and Data preparation

Please follow the folloing links regarding data preparation and previous posts to follow along -

• For Data Preparation - Part 0 - Plotting Using Seaborn - Data …

Part 4 - Plotting Using Seaborn - Heatmap, Lollipop Plot, Scatter Plot

Introduction and Data preparation

Please follow the folloing links regarding data preparation and previous posts to follow along -

• For Data Preparation - Part 0 - Plotting Using Seaborn - Data …

Part 1 - Plotting Using Seaborn - Violin, Box and Line Plot

Introduction and Data preparation

Please follow the folloing links regarding data preparation and previous posts to follow along -

• For Data Preparation - Part 0 - Plotting Using Seaborn - Data …

Part 0 - Plotting Using Seaborn - Data Preparation

Import Preliminaries and datasets

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.pylab as plb
import warnings
warnings.filterwarnings('ignore') …

Nearest Neighbors using L2 and L1 Distance

• Preliminaries
• Distance Matrics
  • L2 Norm
  • L1 Norm
• Nearest Neighbor
  • Using L2 Distance
  • Using L1 Distance
• Predictions
• Errors
• Confusion Matrix
  • Using Pandas
  • From Scratch

Preliminaries

import …

Exception handling in Python

• Try and Except
  • Handle Exceptions
  • Exceptions Attributes
  • Handling Multiple Exceptions
• Else
• Finally

Try and Except

• Handle Exceptions

The following statement will throw an error as string …

Functions in Python - return, scope, args and kwargs

• Return in Function
• Scoping in Function
  • Access global variable in function context
  • Declare a local variable within in a function
  • Declare local variable with same name as in global
  • Using Global …

Break, Continue and Pass in Python

Continue vs Break

Continue

print("The loop will skip the value when value of i is 2 and restart from next value of i - ")
for i in range(0,4):
    if i == 2:
        continue
    else: …

Business Days with Custom Holidays

Importing Packages and Datasets

import pandas as pd

start_date = ['2019-06-03', '2019-06-13', '2019-10-01', '2019-09-01']
end_date =  ['2019-08-31', …

Months between two dates

Importing Packages and Datasets

import pandas as pd
import numpy as np

start_date = ['2019-06-03', '2019-06-13', '2018-11-05', '2019-05-31', '2019-06-01', …

Applying functions over pandas dataframe using apply, applymap and map

Importing Packages and Datasets

import pandas as pd
import numpy as np
data = pd.DataFrame(np.random.rand(4, 3)*100,
                    columns=['Physics','Çhemistry','Maths' …

Filtering using mask and where in pandas

Filtering a dataframe can be achieved in multiple ways using pandas. There are times when you simply need to update a column based on a condition which is true or vice-versa. In pandas dataframe …

String Interpolation in Python

String operations in python, sometimes can be a bit tedious, specially when we need to pass variables within Strings.

Although there are multiple ways to achieve the same, but some of the them are …

Join, Merge, Append and Concatenate

Working with multiple data frames often involves joining two or more tables to in bring out more no. of columns from another table by joining on some sort of relationship which exists within a table …

Attributes, Methods and Functions in python

Understand the concept of attributes, methods and functions under the context of a dataframe

Attributes

Attributes are the features of any object. They can be accessed by following a dot and the name …

Subsetting a dataframe in pandas

Importing packages and datasets

import pandas as pd
# Fetching data from url as csv by mentioning values of various paramters
data = pd.read_csv( …

Indexing and Sorting a dataframe using iloc and loc

There are multiple ways in pandas by which a dataframe can be indexed i.e, selecting particular set of rows and columns from a dataframe. For a detailed description over this topic, once can refer …

Read data into pandas

Provide column names while reading a dataset in pandas

# Import the required modules
import pandas as pd

Reading the dataset using read.csv() function with mentioning column names in names …