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Finance Analysis And Reporting | Finance Analyst Training | Python Data Analytics 2023 | Simplilearn

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Published on 05/26/23 / In How-to & Learning

This tutorial on Finanace Management using Python is the guide to finance analysis and reporting using Pandas, Numpy, Matplotlib and Seaborn modules. This video on Finance Analysis and Reporting will make you learn how to draw plots using pyplot class of matplotlib.

Here we start with:
👉00:00 Finance Management using Python
👉00:48 Quiz Question
👉01:16 Python Skillup Course
👉01:46 Introduction to csv file for data analysis
👉04:16 Installing modules
👉06:00 Hands on Demonstartion
👉14:34 Using head() function
👉15:23 Using drop() function
👉20:03 Using replace() function
👉21:32 Drawing plots using countplot()
👉45:06 Python Certification Course

✅Link to csv file used for analysis: https://drive.google.com/file/....d/1pZKKZk86eivFhOSZz

✅Link to Jupyter Source File: https://drive.google.com/file/....d/1MrCwbrsQqt-goSVLi

✅Pandas is an open-source library designed primarily for working quickly and intuitively with relational or labelled data. It offers a range of data structures and procedures for working with time series and numerical data. This library is built on top of the NumPy library. Pandas is quick and offers its users exceptional performance & productivity.

✅NumPy is an open source and general-purpose array-processing package. It offers a multidimensional array object with outstanding speed as well as tools for interacting with these arrays.

✅Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Most of the Matplotlib utilities lies under the pyplot submodule, and are usually imported under the plt alias:

✅Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.

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