pychallenger

Basic Data Analysis

more coming soon!!!
Data Analysis
Data Science
Big Data
NumPy
matplotlib
Pandas
data visualization
data preparation
data cleaning
data manipulation
data structures
  1. 0/17

    NumPy

    If you want to learn data analysis in Python, you need to learn NumPy, the standard library for numerical data. This course covers array creation, indexing, and boolean indexing.
  2. 0/14

    NumPy II

    Build on your NumPy foundation with array arithmetic, aggregation functions like sum and mean, and array reshaping.
  3. 0/27

    Matplotlib

    Learn how to create line and scatter plots with matplotlib, and customize their appearance with titles, labels, grids, and legends.
  4. 0/10

    Matplotlib II

    Go beyond line plots. Learn to create bar charts, histograms, and pie charts to visualize categorical and distribution data.
  5. 0/14

    pandas

    Learn how to load data into pandas DataFrames, inspect and slice them, filter rows by condition, and compute basic statistics.
  6. 0/13

    pandas II

    Build on your pandas foundation with sorting, groupby aggregations, and techniques for detecting and handling missing values.
  7. 0/23

    Data Analysis Fundamentals

    Tie everything together. Learn the data analysis workflow: explore datasets, count values, derive new columns, and visualize your findings.