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

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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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➡️ About Post Graduate Program In Data Analytics
This Data Analytics Program is ideal for all working professionals and prior programming knowledge is not required. It covers topics like data analysis, data visualization, regression techniques, and supervised learning in-depth via our applied learning model with live sessions by leading practitioners and industry projects.

✅ Key Features
- Post Graduate Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
- 8X higher live interaction in live online classes by industry experts
- Capstone from 3 domains and 14+ Data Analytics Projects with Industry datasets from Google PlayStore, Lyft, World Bank etc.
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✅ Skills Covered
- Data Analytics
- Statistical Analysis using Excel
- Data Analysis Python and R
- Data Visualization Tableau and Power BI
- Linear and logistic regression modules
- Clustering using kmeans
- Supervised Learning

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