This tutorial will introduce the use of Python for statistical data analysis, using data stored as Pandas DataFrame objects. Much of the work involved in analyzing data resides in importing, cleaning and transforming data in preparation for analysis. Therefore, the first half of the course is comp...
The course uses Jupyter Notebook to share all the code. Key Highlights Learn to use Python libraries – Pandas for Data Analysis, NumPy for Numerical Data, Matplotlib for Python Plotting, Seaborn for statistical plots, Plotly for interactive dynamic visualizations, SciKit-Learn for Machine Learning ...
Who should take this course? It is designed for people who want to “move beyond Excel” and write more complex Python codes for data analysis and statistical testing. What we like What we don’t like Interactive exercises. Some content requires a subscription. Real-world examples. Lacks a ...
Statistical Analysis Financial Analysis Data Visualization DataViz Random Variables Sampling Inference Linear Regression Coursera Plus Course Auditing Coursera The Hong Kong University of Science and Technology - HKUST Xuhu Wan Economics & Finance Business Hong Kong Intermediate 4 Weeks 1-4 Hour...
for performing data cleaning and analysis - pandas for basic statistical tools – numpy, scipy for data visualization – matplotlib, seaborn Why Python and how popular is it for Data Science? Python has rapidly become the go-to language in the data science space and is among the first thing...
Featured course from Noble Desktop Learn more & register Data Analytics CertificateLearn The Skills Guarantee™ Learn the essential skills needed to become a Data Analyst or Business Analyst, including data analysis, data visualization, and statistical analysis. Gain practical experience through real-wor...
pandas——Python 数据分析库,包括数据框架(dataframes)等结构Python Data Analysis Library matplotlib——一个 2D 绘图库,可产生出版物质量的图表Python plotting - Matplotlib 2.0.0 documentation scikit-learn——用于数据分析和数据挖掘人物的机器学习算法scikit-learn: machine learning in Python ...
role, such as data cleaning, data manipulation, statistical analysis, and machine learning.By the end of this module, learners will have a good understanding of Python, be proficient in using Jupyter notebooks for data analysis, and comprehend how Python is used to address real-world data ...
[031]4.Py Linear Discriminant Analysis (LDA) I 2023.zh_en 09:58 [032]4.Py K-Nearest Neighbors (KNN) I 2023.zh_en 07:06 [033]5.1 Cross Validation.zh_en 14:02 [034]5.2 K-fold Cross Validation.zh_en 13:34 [035]5.3 Cross Validation the wrong and right way.zh_en ...
This course will introduce you to time series analysis in Python. After learning what a time series is, you'll explore several time series models, ranging from autoregressive and moving average models to cointegration models. Along the way, you'll learn how to estimate, forecast, and simulate...