Pandas Tutorial


data science lessons

Pandas Tutorial - Learn how to manage and analyze data using Python

Pandas is the most popular and powerful tool available to perform the entire Data Analysis Life Cycle.
That is, gathering, preparing, analyzing, and presenting data. With Pandas you can gather data from flat files
like CSV, text, Excel, and JSON.
You can also read in data from the various popular databases like Microsoft SQL Server,
SQLlite, MySQL, Oracle, etc.
Munging or cleaning data is a breeze in Pandas. From functions to clean up strings to functions
that aggregate data, handle missing values, and provide descriptive statistics for further insights into your data. On top
of all this you can present your data using tables and visually impressive charts.
In the following sections we will take you through all the steps to get started coding in Python and Pandas. Don't worry if
you have no programming experience, we have written this guide assuming you are starting from ground zero.


Pandas 101

Pandas DataFrame

The basic building block of Pandas

Pandas Read_CSV

Learn how to read CSV files into Pandas

Pandas GroupBy

How to do GroupBy operation in Pandas

Pandas Merge

How to do simple SQL join operations in Pandas

Pandas Plot

How to create plots and charts in Pandas

Pandas Concat

How to glue DataFrames in Pandas

Pandas Apply

How to Apply functions in Pandas


Pandas Data Analysis Bundle



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Introductory IPython/Jupyter Notebooks for new Pandas Users!

Get your own copy of the most popular Pandas tutorials Hedaro has to offer.

Get a total of 7 tutorials!

  • Dates in Pandas
  • Group By Operations in Pandas
  • Lambdas and Masks
  • Plotting in Pandas
  • Pandas for Excel Developers
  • Pandas for SQL Developers
  • Pivot Tables in Pandas


What will you learn:

  • How to get today's date with timestamp

  • How to get today's date with NO timestamp

  • How to get the timestamp of a date

  • How to get the day of a date

  • How to get the month of a date

  • How to get the year of a date

  • How to get yesterdays date

  • How to get last months date

  • How to get the first day of last month

  • How to get the last day of last month

  • How to get the Monday of last week

  • How to get the Sunday of last week

  • Basic date math

  • How to group by one column

  • How to group by multiple columns

  • How to iterate over a group

  • How to apply built-in functions like sum and std

  • How does group by work

  • How to add a new column to a group

  • How to sum a column but keep the same shape of the df

  • How to perform multiple aggregations at the same time

  • How to choose aggregation methods per column

  • How to add custom labels to multiple aggregations

  • Examples using lambda

  • Which rows are greater than 10

  • Comparisons with lambda

  • Returning Boolean values

  • Lambda with multiple inputs

  • Comparing functions with lambda functions

  • How to plot a line chart

  • How to plot a bar chart

  • How to label the legend

  • How to create a legend

  • How to label the x axis

  • How to label the y axis

  • How to give the chart a title

  • How to create side by side charts

  • How to create dashboards with multiple charts

  • How to size your charts

  • How to choose different colors and line styles

  • How to add a column and sum horizontally

  • How to add a column and compute the average

  • How to add a column and compute the percentage of Total Sales

  • How to sort by a column

  • How to filter by a value

  • How to create a column chart

  • How to create a pivot table

  • How to perform a vlookup

  • How to perform an IF/THEN statement

  • How to declare variables

  • How to update variables

  • How to update a table

  • How to get current date, yesterday, last year

  • How to get first of month or last day of month

  • How to insert into a table from another table

  • How to join two tables

  • How to select n number of rows

  • How to select rows in ascending/descending order

  • How to select unique vales (no dups)

  • How to write a case statement within an update

  • How to check for NULL values

  • How to use the Keyword "IN"

  • How to count all of the rows in a table

  • How to delete contents of a table

  • How to select the smallest/largest value in a column

  • How to string match

  • How to organize a dataframe by specific columns

  • How to fill NaN values

  • How to add sub-totals to the columns and rows

  • How to use the sum function

  • How to use the count function

  • How to use the mean function

  • How to use the max function

  • How to use the min function

  • How to use the len function

  • How to apply different functions to different columns

  • How to apply multiple functions to one column

  • How to apply a custom function

  • How to glue pivot tables together