Python Pandas Tutorial for Absolute Beginners - #1 Intro & Series

Learn programming in Pandas, a Python Library, 100 seconds at a time in this video for absolute beginners. This is video number 1: Pandas Intro and Series.

I know im going fast in this video, please use timestamps below to navigate the video.
Timestamps:
00:00 - introduction
00:14 - purpose of pandas
00:24 - datastructres in pandas
00:36 - using pandas
00:50 - series function
01:01 - adjusting the index
01:21 - mathematical functions
01:45 - adjusting index 2

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Pandas Intro and Series
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Pandas is on of the most common used data analysis library in Python built on top of NumPy.
NumPy is also a python library used for scientific computing, which I covered before
If you want to have a look, check the link in the description down below.
Knowing a little bit of NumPy can help a lot, but is not a prerequisite.

Pandas is well suited for
- loading data. handeling missing data
Insert and delete columns or rows
Merging and joining joining data
And a lot more.

Pandas has two main data structures: Series and Dataframe
A Serie is a 1-dimensional array, just like a numpy array
A DataFrame is a 2 dimensional array also called a matrix
This video is focused on series.

To use pandas start with importing the library.
standard practice is to import the library as ‘pd’
Technically speaking you can choose any name, but pretty much everyone uses ‘pd’ and its also recommended by the official documentation.
Import as pd
To create a pandas serie we use the series function on an array or list. As you can see, pandas indexed the array automatically. With a series the index is by default numbers, just a like a regular python list.
Numbers = [70,80,90,60]
print(data)

With python lists the indexes are always numbers, but Pandas allows you to choose what you want as an index. Lets say the values that I passed were the age of certain employees
We could add custom indexes to our pandas series
print(data2)

We can give a name to our pandas series like this
print(data2)

Just like numpy arrays we can perform mathematical functions
The sum function sums all the values in the series.
The min function retrieves the lowest value in the series
And the max function retrieves the highest value in the series

Pandas series can be combined with python operators
Let’s say we want to validate which values are higher than 70
we can apply the operator like this and check which values are higher than 70
Data3 = data2 70
print(data3)

To check what the indexes are in a pandas series we can use the index function
Finally we can use an index number for multiple values. Here’s an example.
Depending on the case you might want to re-use an index
print(data4)
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🦁 Who are you?
My name is Raza. I am 30. I am an IT - manager right now, but I’ve been an accountant for the majority of my career.
I’m in love with #Python :)

You can find me here:
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