How long might you be stopped for a violation?

Analyzing Police Activity with pandas

Kevin Markham

Founder, Data School

Analyzing an object column

apple

date_and_time         price    volume  change      
2018-01-08 16:00:00  174.35  20567800    down
...                     ...       ...     ...
2018-03-09 16:00:00  179.98  32185200      up

Create a Boolean column: True if the price went up, and False otherwise
Calculate how often the price went up by taking the column mean

apple.change.dtype

dtype('O')

.astype() can't be used in this case

Mapping one set of values to another

Dictionary maps the values you have to the values you want

mapping = {'up':True, 'down':False}

apple['is_up'] = apple.change.map(mapping)

apple

date_and_time         price    volume change  is_up
2018-01-08 16:00:00  174.35  20567800   down  False
...                     ...       ...    ...    ...
2018-03-09 16:00:00  179.98  32185200     up   True

apple.is_up.mean()

0.5

Calculating the search rate

Visualize how often searches were done after each violation type

ri.groupby('violation').search_conducted.mean()

violation
Equipment              0.064280
Moving violation       0.057014
Other                  0.045362
Registration/plates    0.093438
Seat belt              0.031513
Speeding               0.021560

search_rate = ri.groupby('violation').search_conducted.mean()

Creating a bar plot

search_rate.plot(kind='bar')
plt.show()

Bar plot of search rate by violation

Ordering the bars (1)

Order the bars from left to right by size

search_rate.sort_values()

violation
Speeding               0.021560
Seat belt              0.031513
Other                  0.045362
Moving violation       0.057014
Equipment              0.064280
Registration/plates    0.093438
Name: search_conducted, dtype: float64

Ordering the bars (2)

search_rate.sort_values().plot(kind='bar')
plt.show()

Ordered bar plot of search rate by violation

Rotating the bars

search_rate.sort_values().plot(kind='barh')
plt.show()

Horizontal bar plot of search rate by violation

Let's practice!

Analyzing Police Activity with pandas