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Exploratory Data Analysis and Visualization in Python

Python Programming Part 1 & 2

  • Looping
  • Functions
  • Lambda Expressions
  • Methods

Matplotlib Part 1 & 2

  • Subplots
  • Customizing plot appearance

Numpy

  • Creating arrays
  • Indexing and Selection
  • Basic operations

Pandas

  • Subsetting dataframes
  • Working with the Index
  • Missing data
  • Group By
  • Combining dataframes (merge, join, concatenation)
  • Pivot Table

911 Call Exploratory Data Analysis

  • Time Series study with seaborn
  • Heat maps with seaborn

Financial Exploratory Analysis

  • Pairplot with seaborn
  • Moving average line plot
  • Heat maps with seaborn

Country Birth Rate Exploratory Analysis

  • Creating dataframes
  • Merging dataframes
  • Scatterplots with seaborn

** Domestic Gross Percentage Exploratory Analysis**

  • Filtering using isin function
  • Box plot with jitter

Python A-Z Internet Users Exploratory Analysis

  • Subsetting
  • Filtering

Python A-Z Internet Users Data Visualization

  • Seaborn plots
  • Keyword Arguments in Python

Python A-Z Movie Rating Data Visualization

  • Converting variables
  • Stacked histograms
  • KDE plot with seaborn
  • Subplots
  • Building & styling dashboards

Pandas Data Visualization

  • Hex bin
  • Kernel density plot

Ploty & Cufflinks

  • 3D surface plots
  • Spread plots
  • Bubble plots
  • Scatter matrix plots

Plotly Geograhical Plotting

  • USA choropleth map
  • Global choropleth map

Seaborn

  • Distribution plots (histogram, joint plot, rug plot, kde)
  • Categorical plots (bar plot, count plot, box plot, violin plot, strip plot, swarm plot, factorplot))
  • Matrix plots (heat maps, cluster maps)
  • Regression plots (linear model plot, faceted linear model plot)
  • Grids (pairplot, pair grid, facet grid)
  • Customizing style and color

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Data analysis and visualization with PyData ecosystem: Pandas, Matplotlib Numpy, and Seaborn

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