Learn Python Language
Let's start.
Python is a popular
programming language used for a wide range of applications, from web
development and data science to machine learning and artificial intelligence.
Here are some of the basics that you can start with:
Installation: You will need to install Python on your
computer to get started. You can download the latest version of Python from the
official website: https://www.python.org/downloads/
Basic Syntax: Python has a simple and easy-to-understand
syntax that makes it a great language for beginners. You will learn about
variables, data types, operators, and control structures such as if/else
statements, loops, and functions.
Data Structures: Python provides built-in data structures such
as lists, tuples, and dictionaries that allow you to store and manipulate data
in your programs.
Input and Output: You will learn how to read input from the user
and write output to the console or files.
Object-Oriented Programming: Python supports object-oriented programming,
which allows you to organize your code into classes and objects.
Modules and Packages: Python has a vast library of modules and
packages that you can use to extend the functionality of your programs.
Error Handling: You will learn how to handle errors and
exceptions in your programs to make them more robust.
Debugging and Testing: Debugging and testing are crucial parts of
software development. You will learn how to use debugging tools and write unit
tests to ensure that your code works as expected.
There are many resources
available online for learning Python, including video tutorials, online
courses, and books. You can start with the official Python documentation or
online courses such as Codecademy or Coursera.
What is relation between python and
anaconda?
Python and Anaconda are
related but they serve different purposes.
Python is a programming
language that provides a syntax and a set of tools to create software, scripts,
and applications.
Anaconda is a data science
platform that includes Python and many data science-related libraries such as
NumPy, Pandas, Matplotlib, and Scikit-learn. Anaconda provides a distribution
of Python, which is bundled with a collection of data science packages, and an
environment manager to create isolated environments for different projects.
In other words, Anaconda is a
Python distribution that provides a complete data science environment for
developers, while Python itself is just a programming language that can be used
for a wide variety of purposes beyond data science.
By using Anaconda, you can
install and manage different versions of Python along with data science-related
packages and libraries, which can simplify the setup of your data science
projects. Additionally, Anaconda provides an environment manager, which enables
you to create isolated environments for different projects, making it easy to
manage dependencies and avoid conflicts between different packages.
Overall, Python is the
programming language, while Anaconda is a distribution of Python that includes
data science-related packages and an environment manager to help manage different
environments for different projects.
Should I install python first
or anaconda to start learning python. what do you recommend?
If you are new to Python and
want to start learning the language, I would recommend installing Anaconda
first. Anaconda provides a complete data science platform that includes Python
and many popular data science libraries, making it easy to get started with
Python for data analysis and scientific computing.
With Anaconda, you can
install multiple versions of Python and different packages and libraries,
including popular data science packages such as NumPy, Pandas, and Matplotlib,
without having to worry about compatibility issues or conflicts between different
packages. Additionally, Anaconda includes an environment manager, which allows
you to create isolated environments for different projects, making it easy to
manage dependencies and avoid conflicts between packages.
Once you have installed
Anaconda, you can use the Anaconda Navigator interface to launch Python and
other data science tools, or you can use the command-line interface to launch
Python directly.
However, if you prefer to
start with a simpler and more lightweight installation, you can install Python
directly from the official Python website and then add the packages and
libraries you need as you go. This approach requires more manual setup and
management of packages and dependencies but can be a good option for those who
want more control over their installation.
What to do first after installing anaconda.?
After you have installed
Anaconda, the first thing you should do is to launch the Anaconda Navigator,
which is a graphical user interface (GUI) that allows you to manage your
Anaconda installation and launch different data science applications.
To launch the Anaconda
Navigator, you can either search for it in your computer's applications or
launch it from the Anaconda Prompt. To launch it from the Anaconda Prompt,
simply open the Anaconda Prompt and type anaconda-navigator followed by Enter.
Once you have launched the
Anaconda Navigator, you can explore the different data science applications
that are available, including Jupyter Notebook, Spyder, and RStudio. You can
also use the Navigator to create and manage different environments for
different projects.
If you're new to Python, I
would recommend starting with Jupyter Notebook, which is a web-based
interactive development environment (IDE) that allows you to write, run, and
share Python code in a notebook format. Jupyter Notebook is a popular tool for
data analysis and scientific computing, and it's a great way to get started
with Python.
To launch Jupyter Notebook
from the Anaconda Navigator, simply click on the "Launch" button next
to the Jupyter Notebook icon. This will open Jupyter Notebook in your default
web browser, and you can start working with Python code right away.
Ok I have launched
Jupyter notebook what's next?
Having launched Jupyter Notebook, you can start using it to write and run Python code.
Jupyter Notebook allows you
to create and edit notebooks that contain code, text, and multimedia elements
such as images and videos. Each notebook consists of a series of cells, which
can contain either code or markdown text.
To create a new notebook,
click on the "New" button in the top right corner of the Jupyter
Notebook interface and select "Python 3" or any other Python kernel
of your choice. This will open a new notebook with an empty code cell.
You can then start writing
Python code in the cell, and then run it by pressing "Shift + Enter"
or by clicking the "Run" button in the toolbar. Jupyter Notebook will
execute the code in the cell and display the output below the cell.
You can also add new cells to
the notebook by clicking the "+" button in the toolbar, or by using
the keyboard shortcut "Esc + B" to insert a new cell below the
currently selected cell.
As you continue to work with
Jupyter Notebook, you'll discover many other features and capabilities, such as
importing and using Python libraries, plotting data using Matplotlib, and
working with data using Pandas.
A small example for writing a python code in Jupyter?
Here's a simple example of
how to write Python code in Jupyter Notebook:
In Jupyter Notebook, create a
new notebook by clicking on "New" in the top right corner of the
screen and selecting "Python 3".
In the first cell of the
notebook, type the following code:
print("Hello,
World!")
Run the code by clicking the
"Run" button in the toolbar or by pressing "Shift + Enter".
You should see the output "Hello, World!"
printed below the code cell.
That's it! This is a simple
example of how to write and run Python code in Jupyter Notebook. You can use
Jupyter Notebook to write more complex code and to explore data using Python's
data analysis and visualization libraries, such as Pandas and Matplotlib.
You wrote your
first ever code in
python with your help. Move to a few more examples but not difficult ones
Get started with Python. Here
are a few more examples of simple Python code snippets that you can try in
Jupyter Notebook:
Compute the sum of two
numbers:
Python Code is as follows:
a = 5
b = 7
c = a + b
print(c)
In this code, we first assign
the values 5 and 7 to variables a and b, respectively. We then compute the sum
of a and b and store the result in a new variable c. Finally, we print the
value of c, which should be 12.
Compute the average of three numbers:
Python Code is as follows:
x = 3
y = 5
z = 7
avg = (x + y + z) / 3
print(avg)
In this code, we first assign
the values 3, 5, and 7 to variables x, y, and z, respectively. We then compute
the average of these three numbers by adding them together and dividing by 3,
and store the result in a new variable avg. Finally, we print the value of avg,
which should be 5.
Print a list of even numbers:
Python Code is as follows:
for i in range(10):
if i % 2 == 0:
print(i)
In this code, we use a for
loop to iterate over the numbers from 0 to 9. For each number i, we check if
it's even by computing i % 2. If the remainder is 0, then i is even, so we
print it using the print() function. The output should be a list of even
numbers from 0 to 8.
I hope these examples help
you continue your journey with Python!
Let’s try writing python code
in Jupyter
I tried writing following
code in Jupyter:
a=3
b=5
d=3+5
print (D)
When I entered run button, I got following error, (also refer screenshot
below for error)
“NameError
Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_9744\2746299901.py in <module> 2 b=5 3
d=3+5 ----> 4 print (D) NameError: name 'D' is not defined”
Reason for Error
This error is occurring
because you are trying to print the variable D, which has not been defined. In
Python, variable names are case-sensitive, which means that D is not the same
as d.
In your code, you have
defined the variables a, b, and d, but not D. When you try to print D, Python
raises a NameError because it doesn't recognize the name.
To fix this error, you should
change print(D) to print(d), like this:
Tell me some basic commands of python
Sure, here are some basic commands in Python:
print(): Used to print output to the console.
Example: print("Hello, world!")
input(): Used to take input from the user through the console.
Example: name = input("What is your name? ")
if/else statements: Used to create conditional logic in your code.
Example:
pythonCopy code
if x > 10: print("x is greater than 10") else: print("x is less than or equal to 10")
for loops: Used to iterate over a collection of items.
Example:
scssCopy code
for i in range(10): print(i)
while loops: Used to create a loop that continues until a certain condition is met.
Example:
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i = 0 while i < 10: print(i) i += 1
def keyword: Used to define functions in Python.
Example:
pythonCopy code
def add_numbers(x, y): return x + y
These are just a few of the many basic commands available in Python.
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