Creating Histograms
Why Use Histograms?
Histograms are used to visualize the distribution of continuous (numerical) data. They show how data is spread across ranges (bins) and help us:
-
Detect skewness, outliers, or gaps;
-
Understand frequency distribution;
-
Quickly assess if the data is normally distributed or not.
They are best used for variables like price, mileage, or age.
Basic Histogram Syntax in ggplot2
ggplot(data = df, aes(x = variable)) +
geom_histogram()
The x variable must be numeric.
Customize using bins, fill, color, theme, etc.
Example: Distribution of Selling Prices
ggplot(data = df, aes(x = selling_price)) +
geom_histogram(fill = "steelblue", color = "black") +
labs(title = "Distribution of Selling Prices",
x = "Selling Price (in PKR)",
y = "Count") +
theme_minimal()
This plot shows how car prices are distributed. It can highlight if most cars fall in a certain price range.
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Why Use Histograms?
Histograms are used to visualize the distribution of continuous (numerical) data. They show how data is spread across ranges (bins) and help us:
-
Detect skewness, outliers, or gaps;
-
Understand frequency distribution;
-
Quickly assess if the data is normally distributed or not.
They are best used for variables like price, mileage, or age.
Basic Histogram Syntax in ggplot2
ggplot(data = df, aes(x = variable)) +
geom_histogram()
The x variable must be numeric.
Customize using bins, fill, color, theme, etc.
Example: Distribution of Selling Prices
ggplot(data = df, aes(x = selling_price)) +
geom_histogram(fill = "steelblue", color = "black") +
labs(title = "Distribution of Selling Prices",
x = "Selling Price (in PKR)",
y = "Count") +
theme_minimal()
This plot shows how car prices are distributed. It can highlight if most cars fall in a certain price range.
¡Gracias por tus comentarios!
