Matplotlib: How to Prevent X-Axis Labels from Overlapping

Matplotlib showing x-tick labels overlapping

Ok, finally got it working. The trick was to use plt.setp to manually rotate the tick labels. Using fig.autofmt_xdate() did not work as it does some unexpected things when you have multiple subplots in your figure. Here's the working code with its output:

for i, d in enumerate([360, 30, 7, 1]):
    ax = axes.flatten()[i]
    earlycut = now - relativedelta(days=d)
    data = df.loc[df.index>=earlycut, :]
    ax.plot(data.index, data['value'])

    ax.get_xaxis().set_minor_locator(mpl.ticker.AutoMinorLocator())
    ax.get_yaxis().set_minor_locator(mpl.ticker.AutoMinorLocator())

    ax.grid(b=True, which='major', color='w', linewidth=1.5)
    ax.grid(b=True, which='minor', color='w', linewidth=0.75)

    plt.setp(ax.get_xticklabels(), rotation=30, horizontalalignment='right')

fig.tight_layout()

By the way, the comment earlier about some matplotlib things taking forever is very interesting here. I'm using a raspberry pi to act as a weather station at a remote location. It's collecting the data and serving the results via the web. And boy oh boy, it's really wheezing trying to put out these graphics.

How to prevent x-axis labels from overlapping

• The issue in the OP is the dates are formatted as string type. matplotlib plots every value as a tick label with the tick location being a 0 indexed number based on the number of values.
• The resolution to this issue is to convert all values to the correct type, datetime in this case.
  
  • Once the axes have the correct type, there are additional matplotlib methods, which can be used to further customize the tick spacing.
• The answers to What is plotted when string data is passed to the matplotlib API? explain in more detail what happens when string values are passed to matplotlib.
• As of 2014-09-30, pandas has a read_sql function, which has a parse_dates parameter. You definitely want to use that instead.

Original Answer

Here's how you should convert your date string into real datetime objects:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
data_tuples = [
    ('4084036', '1', '2006-12-22 22:46:35'),
    ('4084938', '1', '2006-12-23 16:19:13'),
    ('4084938', '2', '2006-12-23 16:20:23'),
    ('4084939', '1', '2006-12-23 16:29:14'),
    ('4084954', '1', '2006-12-23 16:28:28'),
    ('4250653', '1', '2007-02-12 21:58:53'),
    ('4250657', '1', '2007-03-12 21:58:53')]
datatypes = [('col1', 'i4'), ('col2', 'i4'), ('date', 'S20')]
data = np.array(data_tuples, dtype=datatypes)
col1 = data['col1']

# convert the dates to a datetime type
dates = mdates.num2date(mdates.datestr2num(data['date']))
fig, ax1 = plt.subplots()
ax1.bar(dates, col1)
fig.autofmt_xdate()

Getting a simple list of tuples out of your database cursor should be as simple as...

data_tuples = []
for row in cursor:
    data_tuples.append(row)

However, I posted a version of a function that I use to take db cursors directly to record arrays or pandas dataframes here: How to convert SQL Query result to PANDAS Data Structure?

Hopefully that helps too.

Matplotlib shows x-axis labels incomplete ; how to prevent overlapping?

You could use Date locators and Date formatters.

import numpy
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import pandas

N = 192
numpy.random.seed(N)

dates = pandas.date_range('1/1/2004', periods=N, freq='m')

df = pandas.DataFrame(
    data=numpy.random.randn(N), 
    index=dates,
    columns=['A']
)

fig, ax = plt.subplots()

ax.plot(df.index, df['A'])

ax.xaxis.set_major_locator(mdates.YearLocator())
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y'))

fig.autofmt_xdate()

plt.show()

interval is the interval between each iteration. For example, if interval=2, mark every second occurrence.

import numpy
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import pandas

N = 192
numpy.random.seed(N)

dates = pandas.date_range('1/1/2004', periods=N, freq='m')

df = pandas.DataFrame(
    data=numpy.random.randn(N), 
    index=dates,
    columns=['A']
)

fig, ax = plt.subplots()

ax.plot(df.index, df['A'])
ax.xaxis.set_major_locator(mdates.MonthLocator(interval=5))
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))

fig.autofmt_xdate()

plt.show()

Python, x-axis title is overlapping the tick labels in matplotlib

You could use "Tight Layout" function in matplotlib to solve the issue.

Add the line before you plot the graph, where h_pad will adjust the height, w_pad will adjust the width.

# Adjust x-axis margins
plt.tight_layout(pad=0.4, w_pad=0.5, h_pad=5.0)

And remove this part:

ax.xaxis.labelpad = -10 # Adjust x-axis label position

Result:

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