Adjusting x-axis in matplotlib

Question

I have a range of values for every hour of year. Which means there are 24 x 365 = 8760 values. I want to plot this information neatly with matplotlib, with x-axis showing January, February...... Here is my current code:

from matplotlib import pyplot as plt

plt.plot(x_data,y_data,label=str("Plot"))
plt.xticks(rotation=45)
plt.xlabel("Time")
plt.ylabel("Y axis values")
plt.title("Y axis values vs Time")
plt.legend(loc='upper right')
axes = plt.gca()
axes.set_ylim([0,some_value * 3])
plt.show() 

x_data is a list containing dates in datetime format. y_data contains values corresponding to the values in x_data. How can I get the plot neatly done with months on the X axis? An example:

Answer 1

You could create a scatter plot with horizontal lines as markers. The month is extracted by using the datetime module . In case the dates are not ordered, the plot sorts both lists first according to the date:

#creating a toy dataset for one year, random data points within month-specific limits
from datetime import date, timedelta
import random
x_data = [date(2017, 1, 1) + timedelta(days = i) for i in range(365)]
random.shuffle(x_data)
y_data = [random.randint(50 * (i.month - 1), 50 * i.month) for i in x_data]

#the actual plot starts here
from matplotlib import pyplot as plt
#get a scatter plot with horizontal markers for each data point
#in case the dates are not ordered, sort first the dates and the y values accordingly 
plt.scatter([day.strftime("%b") for day in sorted(x_data)], [y for _xsorted, y in  sorted(zip(x_data, y_data))], marker = "_", s = 900)
plt.show()

Output

The disadvantage is obviously that the lines have a fixed length. Also, if a month doesn't have a data point, it will not appear in the graph.

Edit 1:
You could also use Axes.hlines , as seen here .
This has the advantage, that the line length changes with the window size. And you don't have to pre-sort the lists, because each start and end point is calculated separately. The toy dataset is created as above.

from matplotlib import pyplot as plt
#prepare the axis with categories Jan to Dec
x_ax = [date(2017, 1, 1) + timedelta(days = 31 * i) for i in range(12)]
#create invisible bar chart to retrieve start and end points from automatically generated bars
Bars = plt.bar([month.strftime("%b") for month in x_ax], [month.month for month in x_ax], align = "center", alpha = 0)
start_1_12 = [plt.getp(item, "x") for item in Bars]
end_1_12   = [plt.getp(item, "x") + plt.getp(item, "width") for item in Bars]
#retrieve start and end point for each data point line according to its month
x_start = [start_1_12[day.month - 1] for day in x_data]
x_end = [end_1_12[day.month - 1] for day in x_data]

#plot hlines for all data points
plt.hlines(y_data, x_start, x_end, colors = "blue")
plt.show()

Output

Edit 2:
Now your description of the problem is totally different from what you show in your question. You want a simple line plot with specific axis formatting. This can be found easily in the matplotlib documentation and all over SO . An example, how to achieve this with the above created toy dataset would be:

import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter, MonthLocator

ax = plt.subplot(111)
ax.plot([day for day in sorted(x_data)], [y for _xsorted, y in  sorted(zip(x_data, y_data))], "r.-")
ax.xaxis.set_major_locator(MonthLocator(bymonthday=15))
ax.xaxis.set_minor_locator(MonthLocator())
ax.xaxis.set_major_formatter(DateFormatter("%B"))
plt.show()

Output