Adding Ticks, Labels, and Grid on the X-Axis for Each Day with Pandas Plot

In this article, we’ll explore how to add ticks, labels, and a grid to the x-axis of a pandas plot, specifically for each day. This is useful when dealing with time series data that has multiple dates.

Introduction

When working with time series data in pandas, it’s essential to ensure that the x-axis is properly formatted and readable. One common requirement is to add ticks, labels, and a grid to the x-axis for each day. In this article, we’ll show you how to achieve this using matplotlib’s DayLocator and DateFormatter.

Background

Matplotlib provides several tools for customizing the appearance of plots, including the ability to control the format of the x-axis ticks. The DayLocator class is used to create ticks on occurrences of each day of the month, while the DateFormatter class allows us to specify a format string for the dates.

Problem Statement

The problem with the original code is that it only adds ticks without labels or a grid. To solve this issue, we need to use DayLocator and DateFormatter from matplotlib.dates to create the desired x-axis configuration.

Solution

Here’s an example of how you can modify the original code to add ticks, labels, and a grid on the x-axis for each day:

import pandas as pd
import matplotlib.pyplot as plt 
import matplotlib.dates as mdates
from StringIO import StringIO

# Load data from csv file
mycsv = StringIO("""
time;openBid;highBid;lowBid;closeBid;openAsk;highAsk;lowAsk;closeAsk;volume
2015-12-06T22:00:00.000000Z;1.08703;1.08713;1.08703;1.08713;1.08793;1.08813;1.08793;1.08813;2
2015-12-07T22:00:05.000000Z;1.08682;1.08682;1.08662;1.08662;1.08782;1.08782;1.08762;1.08762;2
2015-12-08T22:01:20.000000Z;1.08683;1.08684;1.08681;1.08684;1.08759;1.08768;1.08759;1.08768;4
2015-12-09T22:01:30.000000Z;1.08676;1.08676;1.08676;1.08676;1.0876;1.0876;1.0876;1.0876;1
2015-12-10T00:03:00.000000Z;1.08675;1.08675;1.08675;1.08675;1.08737;1.08737;1.08737;1.08737;1
2015-12-06T22:03:10.000000Z;1.08675;1.08675;1.08675;1.08675;1.08728;1.08728;1.08728;1.08728;1
2015-12-06T22:03:50.000000Z;1.08676;1.08676;1.08676;1.08676;1.08728;1.08728;1.08728;1.08728;1
""")

# Read data into a pandas DataFrame
df = pd.read_csv(mycsv, delimiter=';', parse_dates=True, index_col='time', header=0)

# Calculate the difference between low and high prices
spr = df['lowAsk']-df['highBid']

# Create a figure and axis object
ax=spr.plot()

# Set the major locator to DayLocator
ax.xaxis.set_major_locator(mdates.DayLocator())

# Set the major formatter to DateFormatter with format string "%a %d"
ax.xaxis.set_major_formatter(mdates.DateFormatter('%a %d'))

# Show the plot
plt.show()

Conclusion

In this article, we showed you how to add ticks, labels, and a grid on the x-axis for each day in a pandas plot. By using DayLocator and DateFormatter, we can customize the format of the x-axis ticks to suit our needs.

We hope that this article has been informative and helpful. If you have any questions or need further clarification, please feel free to ask!

Last modified on 2024-08-11