An analyst has a cuDF DataFrame holding the daily order count for a single warehouse over three years and wants one chart that shows how that count changes from day to day and reveals any seasonal pattern across the period. The horizontal axis represents time and the vertical axis represents the count. Which chart type best fits this goal?
- AA pie chart, with one slice for each day so the relative share of every single day's order count is visible at a glance.
- BA histogram of the order counts, grouping the daily values into bins to show how often each order count level occurs.
- CA line chart, plotting the order count against the date so successive daily values are connected in temporal order. Correct
- DA scatter plot of order count against warehouse identifier, placing one point per day to compare across the sites.
Why A is wrong: A pie chart shows parts of a whole at one moment and is tempting because it encodes proportion, but with hundreds of days it cannot convey order or trend over time and becomes unreadable.
Why B is wrong: A histogram summarises the distribution of the counts and is tempting because the data is numeric, but it discards the date axis entirely and so cannot show change over time or seasonality.
Why C is correct: A line chart connects ordered observations along a continuous time axis, which is exactly how trends and seasonal cycles in a single time series are read; it is the standard choice for one numeric value tracked over time.
Why D is wrong: A scatter plot relates two variables and is tempting for numeric data, but there is only one warehouse here and no second continuous variable, so it cannot display the day-to-day temporal trend.