Lecture "Applied data science: Exploratory data analysis" includes content: definitions; data types; steps in Exploratory Data Analysis (EDA); EDA in real-life practice; . We invite you to consult! | Exploratory Data Analysis Overview 1. Introduction 8. Validation 2. Application 9. Regularisation 3. EDA 10. Clustering 4. Learning Process 11. Evaluation 5. Bias-Variance Tradeoff 12. Deployment 6. Regression review 13. Ethics 7. Classification Lecture outline - Definitions - Data types - Steps in Exploratory Data Analysis EDA - General characteristics of the dataset - Descriptive statistics univariate - Correlation statistics bivariate - Exploratory visualisation - univariate and bivariate - Anomalies - outliers and inliers - Missing values - EDA in real-life practice Definitions Exploratory data analysis can never be the whole story but nothing else can serve as a foundation stone - as the first step. John Tukey 1977 Data Exploratory Analysis Addison-Wesley Exploratory data analysis is an attitude a state of flexibility a willingness to look for those things that we believe are not there as well as those we believe to be there. John Tukey 1977 Data Exploratory Analysis Addison-Wesley The primary aim with exploratory data analysis is to examine the data for distribution outliers and anomalies hypothesis generation by visualising and understanding the data. https chapter 978-3-319-43742-2_15 Structured data vs unstructured data Unstructured data signals images text graphs sounds etc. Structured data - cross-sectional panel time series - Data types nominal ordinal interval ratio transaction latitude longitude etc Structured data types Nominal - labels mutually exclusive no numerical significance may or may not have orders. Ordinal - having order but the difference between variables not defined Structured data types Interval - having order difference between variables defined but don t have a true zero . temperature clock time. For example a glass of water with a temperature of 0 degree does not mean it has no temperature. Ratio - like interval but with a true zero . income age years of education weight. EDA - General characteristics
