the matplotlib and seaborn libraries are imported for data visualization. The sns.set(style=”whitegrid”) line sets the style of the seaborn plots to a white grid background. Subsequently, a matplotlib figure (fig) and axis (ax) are created, specifying a size of 20 units in width and 5 units in height.
The main focus of this code is on visualizing the temporal distribution of crimes. It utilizes a bar plot (barplot1) to display the number of crimes versus the date. The data for the plot is derived from the previously created DataFrame (crime_count_by_date). Specifically, the first 30 dates with the maximum number of crimes are selected using iloc[:30, :]. The bar plot is configured to show these date-crime count relationships, with the bars colored in green.
To enhance the readability of the plot, axis labels are set with ax.set(ylabel=”Number of Crimes”, xlabel=”Date”). Additionally, the x-axis labels (dates) are rotated by 45 degrees for better visibility, and their alignment is adjusted to the right. The font weight is set to ‘light’, and the font size is increased to ‘large’, ensuring that the x-axis labels remain legible even with the rotation.
Overall, this code segment creates a visually informative bar plot that effectively communicates the temporal patterns of crimes, highlighting the specific dates with the highest crime counts in the dataset.