Quantitative data uses numeric values (discrete and continuous). Qualitative data consists of categorical and ordinal characteristics. Graph choice depends on data type and measurement
Histograms visualize numerical data distribution using bars. Unlike bar plots, histograms group numbers into ranges. Histograms help find outliers in datasets
Computes and plots histogram using numpy.histogram. Supports arrays, lists, and 2D ndarrays as input. Returns tuple with n, bins, and patches for array input
Frequency is the number of times an event has occurred in an experiment. Cumulative frequency is the total of absolute frequencies below a certain point. Relative frequency is absolute frequency normalized by total events
Histograms visualize data distribution by counting values in bins. Function requires data and number of bins specification. Useful for identifying patterns and outliers in numerical data
Select data and choose Insert > Statistic Chart > Histogram. Use Chart Design and Format tabs for customization. Set By Category option for text-based categories. Choose Automatic or manual bin width settings. Configure overflow and underflow bins