Building Solutions on Data Analysis with Python and Jupyter Notebook

To collect, analyze, and organize data to make future predictions, and make informed data-driven decisions using Python and Jupyter Notebooks.
Jupyter Notebook is an open-source web application that provides an interactive computational environment. It generates documents that compile inputs (code) and outputs into a single file (notebooks). With Jupyter Notebook, you can create an interactive document that can be shared, reused, and edited by others by combining code, comments, multimedia, and visualizations.

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Feature of Jupyter Notebook

Libraries we can use

Pandas
NumPy
Matplotlib
Seaborn
SciPy
Sci-kit learn

Functions in Jupyter Notebook

Exchange notebooks

You may now share your notebooks with others using email, Dropbox, GitHub, and the Jupyter Notebook Viewer thanks to this feature.

Producing Interactive Results

With the help of this functionality, your code can now generate elaborate and interactive output including HTML, pictures, videos, LaTeX, and unique MIME types.This comprises figures produced by the library that are of publishing quality and can be included inline. Due to LateX, mathematical notations can be easily added and rendered by MathJax.

Easily Removed

Now that you can edit the content before publishing your book online, you can also edit the code only, allowing the image and other outputs to still appear

Code Execution

Additionally, this has the capability of executing scripts directly from the browser while keeping track of computation results in the code that originally generated them.

Markdown

Rich text can be edited in-browser using the Markdown markup language, which is not just restricted to plain text but also gives commentary for the code. To give your postings cool effects, you may also embed photos, HTML, and other outputs inside them.

Language Selection Varieties

Since the notebook supports more than 40 programming languages, including Python, R, Julia, and Scala, you can select the language you like.

Why Use a Jupyter Notebook?

1 All in one Place

In a single document, you might combine code, text, photos, animations, plots, maps, figures, GUI, and videos.

2 Programming languages

Over 40 programming languages, including R, Python, JavaScript, Haskell, and others, are supported by Jupyter notebooks.

3 Simple to convert and share

Because notebooks are saved in the JSON format and include a unique application that can convert them into HTML and PDF, sharing them is simple.

4 Easy Customization

The Jupyter interface makes it simple to design a completely unique experience.

5 Powerful Learning and Teaching Tools

By utilizing features like IPython Blocks and others, it can be used for teaching in addition to data analysis or scientific study.

6 Integration of Big Data

You can use various big data tools with it, including Scala and Apache Spark.

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Founder, Studio SWEAT onDemand

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At BitCot, I worked with Raj and his team, they are brilliant, I discussed the concept with Raj, he really helped me to map out the plan & strategy to get my concept into a real software platform. If you have an idea and you want to make it real, I would recommend Raj and his team. They are affordable, save my time, and map out the right software for me.

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Founder, Biglio

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Founder, Poured

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Building Solutions on Data Analysis with Python and Jupyter Notebook

Jupyter Notebook Services

Data importing

Data pre-processing

Data cleansing

Statistical analysis

Exploratory data analysis

Data Visualization

Machine learning Model

Data Automation

Feature of Jupyter Notebook

Code sharing

Live interactions with code

Documenting code samples

Data visualizations

Libraries we can use

Pandas

NumPy

Matplotlib

Seaborn

SciPy

Sci-kit learn

Functions in Jupyter Notebook

Exchange notebooks

Producing Interactive Results

Easily Removed

Code Execution

Markdown

Language Selection Varieties

Tools that We Use

Python

Jupyter Notebook

Pycharm

Google colab

Why Use a Jupyter Notebook?

Our Clients