02. Exploratory Data Analysis (EDA) in Python - Part 2 | Machine Learning смотреть онлайн

#codersarts #EDA #exploratorydataanalysis #ML #datascience #dataanalysis #datapreprocessing
In this video we will continue to work on the dataset, we will visualize the data and see what univariate, bivariate and multivariate analysis is.

Univariate analysis refers to the analysis of a single variable in isolation. It is a statistical analysis technique that is used to examine the distribution, central tendency, and variability of a single variable. Examples of univariate analysis techniques include measures of central tendency (mean, median, mode), measures of variability (standard deviation, variance), frequency distributions, and histograms.

Bivariate analysis, on the other hand, involves the analysis of two variables simultaneously. It is a statistical analysis technique that is used to examine the relationship between two variables. Examples of bivariate analysis techniques include correlation analysis, scatter plots, and contingency tables.

Timestamps for important topics:
00:00:00 What we’ll learn in this video.
00:00:07 Histogram (pandas)
00:04:05 Histogram (seaborn)
00:05:38 BoxPlot (pandas)
00:06:35 BoxPlot (seaborn)
00:09:03 Heatmap
00:12:58 Scatterplot
00:17:59 Univariate Analysis
00:18:36 Bivariate Analysis
00:18:55 Multivariate Analysis


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