Tukukkk

jupyter notebook 5.2.2

Python 3.6.4

pandas 0.22.0

matplotlib 2.2.2

Hi I'm trying to present and format a histogram in a jupyter notebook based on hour and minute log data retrieved from a hadoop store using Hive SQL.

I'm having problems with the presentation. I'd like to be able to set the axes from 00:00 to 23:59 with the bins starting at zero and ending at the next minute. I'd like half hourly tick marks. I just can't see how to do it.

The following pulls back 2 years data with 1440 rows and the total count of events at each minute.

%%sql -o jondat

select eventtime, count(1) as cnt

from logs.eventlogs

group by eventtime

The data is stored as a string but is hour and minute hh:mm, however it appears to be being auto converted as sysdate plus timestamp by the notebook, I have been playing with the data in this format and others.

If I strip out the colons I get

df.dtypes



eventtime int64

cnt int64

and if I use a dummy filler like a pipe I get

eventtime object

cnt int64

If I leave the colon in with colons I get

eventtime datetime64

cnt int64

which is what I am currently using.

...

2018-11-22 00:27:00 32140

2018-11-22 00:28:00 32119

2018-11-22 00:29:00 31726

...

2018-11-22 23:30:00 47989

2018-11-22 23:31:00 40019

2018-11-22 23:32:00 40962

...

I can then plot the data

%%local



import pandas as pd

import matplotlib

import matplotlib.pyplot as plt

import datetime as dt

import mateplotlib.dates as md



xtformat = md.DateFormatter('%H:%M')



plt.rcParams['figure.figsize'] = [15,10]

df = pd.DataFrame(jondat)



x=df['eventtime']

b=144

y=df['cnt']



fig, ax=plt.subplots()



ax.xaxis_date()



ax.hist(x,b,weights=y)

ax.xaxis.set_major_formatter(xtformat)



plt.show(ax)

Currently my axes start well before and after the data and the bins are centered over the minute which is more of a pain if I change the number of bin. I can't see where to stop the auto-conversion from string to datetime and I'm not sure if I need to in order to get the result I want.

Is this about formatting my eventtime and setting the axes or can I just set the axes easily irrespective of the data type. Ideally the labelled ticks would be user friendly

This is the chart I get with 144 bins. As some of the log records are manual the 1440 bin chart is "hairy" due to the tendency for the manual records being rounded. One of the things I am experimenting with is different bin counts.

Thanks to https://stackoverflow.com/users/4124317/importanceofbeingernest who gave me enough clues to find the answer.

%%local



import pandas as pd

import matplotlib

import matplotlib.pyplot as plt

import datetime as dt

import mateplotlib.dates as md



plt.rcParams['figure.figsize'] = [15,10]

df = pd.DataFrame(jondat)



xtformat = md.DateFormatter('%H:%M')

xtinter = md.MinuteLocator(byminute=[0], interval=1)

xtmin = md.MinuteLocator(byminute=[30], interval=1)





x=df['eventtime']

b=144

y=df[cnt']



fig, ax=plt.subplots()



ld=min(df['eventtime'])

hd=max(df['eventtime'])



ax.xaxis_date()



ax.hist(x,b,weights=y)

ax.xaxis.set_major_formatter(xtformat)

ax.xaxis.set_major_locator(xtinter)

ax.xaxis.set_minor_locator(stmin)

ax.set_xlim([ld,hd])



plt.show(ax);

This lets me plot the chart tidily and play with the bin setting to see how much it impacts the curve both for presentation on a dashboard and to help think about categorization into time bands for analysis of even types by time.