# drawing secondary x axis for months: a better way?

I often have to make graphs with time series, with each point being
the start of a week. Below is the result I wish:

``````![bjgehhcg.png|300x300](upload://7wTFfwWpF1MZuncTMy0xvd3VHOH.png)

However, in order to make the secondary x axis the the month labels,
``````

I need something like 40 lines of code. My strategy consists in
first drawing the rates in the normal way and using matplotlib’s
dateFormatter to set the week numbers. That part is easy.

``````In order to draw the x axis below to show when the weeks occur, I
``````

draw two more lines, and makes these lines invisible. The first line
has as the x points the start of each month, and the y values as the
corresponding rate. The second line has as its x value the middle of
each month, with the corresponding y value.

``````Below is my code. I have to use such a graph quite often--so often,
``````

in fact, that if I don’t find an easier way to make the secondary x
axis, I will store the code in my own library for re-use. Does
anyone know of a simpler, more elegant way?

``````Thanks!

Paul

import matplotlib

import matplotlib.pyplot as plt

import numpy as np

import matplotlib.dates

from datetime import datetime

from datetime import timedelta

def unique_months(dates, rates):

"""

returns two lists, one of the first time a month occurs, the
``````

second, the

``````    rates representing that month

"""

y = [rates]

temp = dates - timedelta(days=dates.day)

months = [temp]

found = [dates.month]

counter = 0

for  d in dates:

month = d.month

if month not in found:

new_date = d - timedelta(days=d.day)

months.append(new_date)

y.append(rates[counter])

found.append(month)

counter += 1

return (months, y)

def half_months(dates, defects):

"""

returns two lists, one the middle of the month occurs, the
``````

second, the

``````    rates representing that month

"""

months, y = unique_months(dates, defects)

new_months =[]

new_y = []

counter = 0

for m in months:

new_date = m - timedelta(days=m.day) + timedelta(days=15)

if new_date <= months[-1]:

new_months.append(new_date)

new_y.append(y[counter])

counter += 1

return new_months, new_y

dates = [datetime(2012,8,19), datetime(2012,8,26),datetime(2012, 9,
``````

3), datetime(2012,9,10), datetime(2012,9,17), datetime(2012,9,24),

``````        datetime(2012,10,1), datetime(2012,10,8)]

rates = [2,3,4,2,5,3,7,2]

fig = plt.figure()

fig.set_size_inches(3,3)

x1, y1 = unique_months(dates, rates)

ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey',
``````

alpha=0.5)

``````ax.set_axisbelow(True)

# plot dates and rates

ax.plot(dates, rates)

ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%W'))

x2, y2 = half_months(dates, rates)

# add tick marks for start of month

# x1 starts at first of each mont; y1 doesn't matter

newax.spines['bottom'].set_position(('outward', 25))

newax.patch.set_visible(False)

newax.yaxis.set_visible(False)

newax.plot_date(x1, y1,  visible=False)

newax.xaxis.set_major_locator( matplotlib.dates.MonthLocator())

newax.set_xticklabels([])

# set labels for months, inbetween tick marsk

# x2 is 15th of each month

axmlab.spines['bottom'].set_position(('outward', 25))

axmlab.patch.set_visible(False)

axmlab.yaxis.set_visible(False)

axmlab.plot_date(x2, y2,  visible=False)

axmlab.xaxis.set_major_formatter(
``````

matplotlib.dates.DateFormatter(’%b’))

axmlab.xaxis.set_major_locator(matplotlib.dates.DayLocator(bymonthday=1))

``````# get rid of tick marks for this axis

for i, line in enumerate(axmlab.get_xticklines() +
``````

newax.get_yticklines()):

``````    line.set_visible(False)

axmlab.plot_date(x2, y2,  visible=False)

axmlab.xaxis.set_major_locator( matplotlib.dates.MonthLocator())

plt.xlabel('Week in Year')

ax.set_ylabel('Rates')

plt.savefig('temp.png', dpi=100)``````

Don't have time to prove that I can reproduce what you want, but
try parasite axes with axes_grid1: the example is for one on the right-hand side, but I think it'll do what you want.

http://matplotlib.org/mpl_toolkits/axes_grid/users/overview.html#axisartist-with-parasiteaxes

M

···

On 10/8/12 11:03 PM, Paul Tremblay wrote:

I often have to make graphs with time series, with each point being the
start of a week. Below is the result I wish:

However, in order to make the secondary x axis the the month labels, I
need something like 40 lines of code. My strategy consists in first
drawing the rates in the normal way and using matplotlib's dateFormatter
to set the week numbers. That part is easy.

In order to draw the x axis below to show when the weeks occur, I draw
two more lines, and makes these lines invisible. The first line has as
the x points the start of each month, and the y values as the
corresponding rate. The second line has as its x value the middle of
each month, with the corresponding y value.

Below is my code. I have to use such a graph quite often--so often, in
fact, that if I don't find an easier way to make the secondary x axis, I
will store the code in my own library for re-use. Does anyone know of a
simpler, more elegant way?

A bit of searching gave me this much simpler solution:

import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import datetime
import matplotlib.dates as m_dates
import matplotlib.ticker as ticker

def make_month_axis(dates, y, ax, fig):

newax.spines['bottom'].set_position(('outward', 25))
newax.patch.set_visible(False)
newax.yaxis.set_visible(False)
newax.plot_date(dates, y, visible=False)

newax.xaxis.set_major_locator(m_dates.MonthLocator())
newax.xaxis.set_minor_locator(m_dates.MonthLocator(bymonthday=15))

newax.xaxis.set_major_formatter(ticker.NullFormatter())
newax.xaxis.set_minor_formatter(m_dates.DateFormatter('%b'))

for tick in newax.xaxis.get_minor_ticks():
tick.tick1line.set_markersize(0)
tick.tick2line.set_markersize(0)
tick.label1.set_horizontalalignment('center')

start = datetime.datetime(2012, 8, 26)
dates = [start]
for i in range(1,10):
dates.append(dates[-1] + datetime.timedelta(days=7))
y = np.random.normal(10, 5, len(dates))
fig = plt.figure()
ax.plot(dates, y)
ax.xaxis.set_major_formatter( matplotlib.dates.DateFormatter('%W'))
make_month_axis(dates = dates, y = y, ax = ax, fig = fig)

plt.show()

Paul

···

On 10/8/12 11:03 PM, Paul Tremblay wrote:

I often have to make graphs with time series, with each point being the start of a week. Below is the result I wish:

However, in order to make the secondary x axis the the month labels, I need something like 40 lines of code. My strategy consists in first drawing the rates in the normal way and using matplotlib's dateFormatter to set the week numbers. That part is easy.

In order to draw the x axis below to show when the weeks occur, I draw two more lines, and makes these lines invisible. The first line has as the x points the start of each month, and the y values as the corresponding rate. The second line has as its x value the middle of each month, with the corresponding y value.

Below is my code. I have to use such a graph quite often--so often, in fact, that if I don't find an easier way to make the secondary x axis, I will store the code in my own library for re-use. Does anyone know of a simpler, more elegant way?

Thanks!

Paul

import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.dates
from datetime import datetime
from datetime import timedelta

def unique_months(dates, rates):
"""
returns two lists, one of the first time a month occurs, the second, the
rates representing that month

"""
y = [rates]
temp = dates - timedelta(days=dates.day)
months = [temp]
found = [dates.month]
counter = 0
for d in dates:
month = d.month
if month not in found:
new_date = d - timedelta(days=d.day)
months.append(new_date)
y.append(rates[counter])
found.append(month)
counter += 1
return (months, y)

def half_months(dates, defects):
"""
returns two lists, one the middle of the month occurs, the second, the
rates representing that month

"""
months, y = unique_months(dates, defects)
new_months =[]
new_y = []
counter = 0
for m in months:
new_date = m - timedelta(days=m.day) + timedelta(days=15)
if new_date <= months[-1]:
new_months.append(new_date)
new_y.append(y[counter])
counter += 1
return new_months, new_y

dates = [datetime(2012,8,19), datetime(2012,8,26),datetime(2012, 9, 3), datetime(2012,9,10), datetime(2012,9,17), datetime(2012,9,24),
datetime(2012,10,1), datetime(2012,10,8)]
rates = [2,3,4,2,5,3,7,2]
fig = plt.figure()
fig.set_size_inches(3,3)
x1, y1 = unique_months(dates, rates)
ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5)
ax.set_axisbelow(True)
# plot dates and rates
ax.plot(dates, rates)
ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%W'))

x2, y2 = half_months(dates, rates)

# add tick marks for start of month
# x1 starts at first of each mont; y1 doesn't matter
newax.spines['bottom'].set_position(('outward', 25))
newax.patch.set_visible(False)
newax.yaxis.set_visible(False)
newax.plot_date(x1, y1, visible=False)
newax.xaxis.set_major_locator( matplotlib.dates.MonthLocator())
newax.set_xticklabels([])

# set labels for months, inbetween tick marsk
# x2 is 15th of each month
axmlab.spines['bottom'].set_position(('outward', 25))
axmlab.patch.set_visible(False)
axmlab.yaxis.set_visible(False)
axmlab.plot_date(x2, y2, visible=False)
axmlab.xaxis.set_major_formatter( matplotlib.dates.DateFormatter('%b'))
axmlab.xaxis.set_major_locator(matplotlib.dates.DayLocator(bymonthday=1))
# get rid of tick marks for this axis
for i, line in enumerate(axmlab.get_xticklines() + newax.get_yticklines()):
line.set_visible(False)
axmlab.plot_date(x2, y2, visible=False)
axmlab.xaxis.set_major_locator( matplotlib.dates.MonthLocator())

plt.xlabel('Week in Year')
ax.set_ylabel('Rates')
plt.savefig('temp.png', dpi=100)