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01. Descriptive Statistics

<p><strong>Descriptive Statistics</strong></p><ul><li><p>This workflow accesses and preprocesses Eurostat data.</p></li><li><p>It shows how to compute descriptive statistics for univariate and bivariate data.</p></li><li><p>It introduces visualization techniques, useful in statistical analysis.</p></li><li><p>[Optional] It shows some operations in Python and R.</p></li></ul>

URL: Population and social conditions > Police records on criminal offences (Eurostat dataset) https://ec.europa.eu/eurostat/databrowser/view/crim_off_cat__custom_12750045/default/table?lang=en

Descriptive Statistics

Univariate vs. Bivariate

1. Access and preprocess

2. Summarize

3. Visualize

Univariate
Bivariate


Range
GroupBy
Data Explorer
Single country selector
Statistics View
Mode
GroupBy
Missing toMedian
Missing Value
Statistics
Filter outcolumns with>50% missing
Missing Value Column Filter
Intentional homicide
Histogram
Color Manager
Summary stats fornumeric columns
Python Script
Linear Correlation
Rank Correlation
Computecorrelation matrix
R Snippet
Covariance
GroupBy
Corruption, bribery andmoney laundering by country
Bar Chart
Histograms
Python View
Intentional homicide by country
Density Plot
Frauds vs acts against computersystems
Scatter Plot
Read sheets of Eurostatdata on police recordsof criminal offences2012-2022
Read Excel Sheet Names
Intentional homicide, sexual violence, robbery, fraud by country
Box Plot
Country selector
Boxplot
R View (Table)
Clean and parse datasetRetain only EU countries
Data access and preprocessing

Nodes

Extensions

Links