Exercise

# EDA: Plot all your data

To get a graphical overview of a data set, it is often useful to plot all of your data. In this exercise, plot all of the splits for all female swimmers in the 800 meter heats. The data are available in a Numpy arrays `split_number`

and `splits`

. The arrays are organized such that `splits[i,j]`

is the split time for swimmer `i`

for `split_number[j]`

.

Instructions

**100 XP**

- Write a
loop, looping over the set of splits for each swimmer to:`for`

- Plot the split time versus split number. Use the
`linewidth=1`

and`color='lightgray'`

keyword arguments.

- Plot the split time versus split number. Use the
- Compute the mean split times for each distance. You can do this using the
`np.mean()`

function with the`axis=0`

keyword argument. This tells`np.mean()`

to compute the means over rows, which will give the mean split time for each split number. - Plot the mean split times (y-axis) versus split number (x-axis) using the
`marker='.'`

,`linewidth=3`

, and`markersize=12`

keyword arguments. - Label the axes and show the plot.