Plot time without date in matplotlib or seaborn

Question

Hi I am working on a categorical data. I want to see device behavior on a given day. I have these as my dataframe:

On toronto_time, I have a datetime64[D]. I previously used dt.time to remove the date. However, it presents a datatype problem which makes it a type object and not datetime64[D]. Converting it again with pd.to_datetime will add a date on itself.

So I left it with the original:

       toronto_time             description
0      2018-09-08 00:00:50      STATS
1      2018-09-08 00:01:55      STATS
2      2018-09-08 00:02:18      DEV_OL
3      2018-09-08 00:05:24      STATS
4      2018-09-08 00:05:34      STATS
5      2018-09-08 00:06:33      CMD_ERROR

I tried plotting it with seaborn with these codes:

import matplotlib.pyplot as plt
import matplotlib.dates as md
import seaborn as sns

plt.style.use('seaborn-colorblind')
plt.figure(figsize=(8,6))
sns.swarmplot('toronto_time', 'description', data=df);
plt.show()

However the visualization is compressed on that day. I want to remove the day in the xlabel also stretch them according to hours (0:00 to 24:00)

This is what I got:

Answer 1

I'm not sure why you want the minutes and seconds on the graph if your ticks are only on the hour? But you can do it by setting a formatter for your axis. Although I would suggest also changing you axis limits if you're looking for ticks by the hour.

import pandas as pd

import matplotlib.pyplot as plt
import matplotlib.dates as md
import seaborn as sns

df = pd.DataFrame({'toronto_time': ['2018-09-08 00:00:50',
                                    '2018-09-08 01:01:55',
                                    '2018-09-08 02:02:18',
                                    '2018-09-08 03:05:24',
                                    '2018-09-08 04:05:34',
                                    '2018-09-08 05:06:33'], 
                    'description': ['STATS', 'STATS', 'DEV_OL', 'STATS', 'STATS', 'CMD_ERROR']})
df['toronto_time'] = pd.to_datetime(df['toronto_time'], format='%Y-%m-%d %H:%M:%S')

plt.style.use('seaborn-colorblind')
fig, ax = plt.subplots(figsize=(8,6))
sns.swarmplot('toronto_time', 'description', data=df, ax=ax)
ax.set_xlim(df['toronto_time'].min()-pd.Timedelta(1,'h'),
            df['toronto_time'].max()+pd.Timedelta(1,'h'))
ax.xaxis.set_major_formatter(md.DateFormatter('%H:%M:%S'))

plt.show()

Here's a nice example showing how to use a locator to define how the ticks are spaced as well: http://leancrew.com/all-this/2015/01/labeling-time-series/