4.55 (18 reviews)
☑ Project on data analysis.
☑ Data visualization using various plots like line plot, scatter plot, bar plot, pie plot, suplots etc and multiple plots in same graphs and many things
☑ Pandas (Series, DataFrames creation, and operations on them in deep) and working on Datasets.
☑ Working with multidimensional array
☑ Working with mathematical operations and various Numpy functions
☑ Installation of Jupyter Notebook using anaconda
☑ Indexing and slicing in deep using both Numpy and Pandas (i.e. loc and iloc)
☑ Axis in 2D and 3D array
In this course, you'll get very well knowledge of Numpy, Pandas, and Matplotlib with a project. You will learn all the essential things which are needed in data science and data analysis.
By the end of this course you will learn:
What is Numpy and how to use it?
You'll learn how to download install Anaconda.
Learn about 1D, 2D, 3D arrays, how to create them, accessing them, changing them.
Learn how Numpy array is better than a simple List with code.
Learn axis in 2D array and 3D array which is too confusing to understand.
Learn various Mathematical operations that you can perform on Numpy arrays like Addition, Subtraction, Multiplication, Division, Power, sin, cos, tan, Natural log, log base2, log base 10, etc.
Learn Various Numpy functions like vertical stacking, horizontal stacking, mean, sum, variance, standard deviation.
Learn Indexing and Slicing.
We'll do an exercise in which we learn to solve different Numpy related questions.
What is Pandas and how it is useful in data analysis?
Learn about the Series Data Structure, create them with a tuple, list, and dictionary.
Querying a Series
Learn Indexing and Slicing using loc and iloc in 1D, 2D, and 3D arrays.
Learn the DataFrame Data Structure, create them, analyze them, accessing them, etc
Learn Reading data from files.
Learn Indexing DataFrames.
Learn to handle Missing Values
Learn what is Matplotlib, why, and how to use it.
Learn the Line plot and all operation on that plot like adding and changing the style of markers, legend, shape, face color, etc.
Setting x and y-axis and use your data on the x and y-axis.
Learn Pie Plot.
Learn the Scatter Plot.
Learn Bar plot
4. Data Analysis Project
In this project, you'll be able to learn:
how to handle new data.
how to read datasets.
how to merge two datasets.
Removing unnecessary rows and columns.
Arrange dataset according to your need.
Plot the datasets.
Barplot with subplots.
Barplot with multiple plots in a single diagram.
With Python code notebooks, you will be excellently prepared for a future in data science.
Introduction about my course
Introduction to Numpy (1)
Installation of Jupyter notebook with anaconda (2)
Multidimensional array (03)
Accessing array elements (4)
Axis in 2D array (5)
Axis in 3D array (6)
Numpy Quiz 01
Mathematical operations (8)
Various Numpy functions (9)
Indexing and slicing (10)
Numpy array vs simple list (11)
Numpy Quiz 02
Solved exercise Problems (12)
Introduction to Pandas (1)
Querying Series (3)
Accessing elements (5)
Reading data from File (6)
Querying DataFrame (7)
Indexing DataFrame (8)
Missing value (9)
Introduction to Matplotlib (01)
Adding color to line (02)
Marker Face color (04)
Changing line style (05)
Settings X and Y-axis (06)
Scatter Plot (7)
Pie Plot (9)
Data Analysis Project
Data Analysis Project
it is one of the best course of data analysis and visualization for beginners. instructor explain all the concept very well