What you'll learn:
- How to Download and Install Jupyter Notebook
- Working with Numpy for Numerical Computing
- Working with Array in Numpy
- Management of data
- Working with Pandas for data manipulations
- Series and DataFrames
- Reading files using Pandas
- Data Visualization Using Matplotlib Library
- Plotting Histogram, Bargraph, Scatter Plot, Boxplot, Pie Chart and many more
If you are looking to make a career as a Data Scientist, Data Analyst, Machine Learning Expert using Python, then Numpy, Pandas and Matplotlib library is very important to learn in today's scenario. In this course, you will get a detailed explanation of topics and functions related to Numpy, pandas and matplotlib library. After this course, you can able to do Data Manipulation and Data Visualization. You can say these tools are the ladder for the Data Scientist.
Important Feature of this course is as follows:
1. Every topic is covered practically.
2. Explained in very easy language.
3. Non-Programming background can also understand easily
4. Demonstrated in a simple way so that you can do the same by watching videos.
For Data Science aspirants, this is the best course. Nowadays Data Visualization is an important tool to make decisions in organizations. Here using matplotlib library you can easily visualize the data using histogram, bar chart, pie chart, scatter diagram and many more.
Topics Covered in Numpy:
1. Numpy Array
2. Numpy indexing and Slicing
3. Copy vs View
4. Numpy Array Shape, Reshape
5. Numpy Array Iterating
6. Numpy Array joining and Merging
7. Splitting , Searching and Sorting
8. Filtering
9. Random Module
Topics Covered in Pandas:
1. Series
2. DataFrame
3. Import Files/Dataset
4. Merging , Joining and Concatenating
5. Analyzing Data
6. Cleaning Data
7. Data Manipulation
Topics Covered in Matplotlib:
1. Importance of Data Visualization
2. Type of Data Visualization
3. Concepts of matplotlib Library
4. Line Plotting
5. Histogram
6. Bar Plot
7. Scatter Plot
8. Pie Chart
9. Box Plot
10. Area Chart
