python – Plot a horizontal line using matplotlib

Youre looking for axhline (a horizontal axis line). For example, the following will give you a horizontal line at y = 0.5:

import matplotlib.pyplot as plt
plt.axhline(y=0.5, color=r, linestyle=-)
plt.show()

If you want to draw a horizontal line in the axes, you might also try ax.hlines() method. You need to specify y position and xmin and xmax in the data coordinate (i.e, your actual data range in the x-axis). A sample code snippet is:

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(1, 21, 200)
y = np.exp(-x)

fig, ax = plt.subplots()
ax.plot(x, y)
ax.hlines(y=0.2, xmin=4, xmax=20, linewidth=2, color=r)

plt.show()

The snippet above will plot a horizontal line in the axes at y=0.2. The horizontal line starts at x=4 and ends at x=20. The generated image is:

python – Plot a horizontal line using matplotlib

Use `matplotlib.pyplot.hlines`:

Plot multiple horizontal lines by passing a list to the y parameter.
y can be passed as a single location: y=40
y can be passed as multiple locations: y=[39, 40, 41]
If youre a plotting a figure with something like fig, ax = plt.subplots(), then replace plt.hlines or plt.axhline with ax.hlines or ax.axhline, respectively.
matplotlib.pyplot.axhline can only plot a single location (e.g. y=40)
See this answer for vertical lines with .vlines

`plt.plot`

import numpy as np
import matplotlib.pyplot as plt

xs = np.linspace(1, 21, 200)

plt.figure(figsize=(6, 3))
plt.hlines(y=39.5, xmin=100, xmax=175, colors=aqua, linestyles=-, lw=2, label=Single Short Line)
plt.hlines(y=[39, 40, 41], xmin=[0, 25, 50], xmax=[len(xs)], colors=purple, linestyles=--, lw=2, label=Multiple Lines)
plt.legend(bbox_to_anchor=(1.04,0.5), loc=center left, borderaxespad=0)

`ax.plot`

import numpy as np
import matplotlib.pyplot as plt

xs = np.linspace(1, 21, 200)
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(6, 6))

ax1.hlines(y=40, xmin=0, xmax=len(xs), colors=r, linestyles=--, lw=2)
ax1.set_title(One Line)

ax2.hlines(y=[39, 40, 41], xmin=0, xmax=len(xs), colors=purple, linestyles=--, lw=2)
ax2.set_title(Multiple Lines)

plt.tight_layout()
plt.show()

Time Series Axis

xmin and xmax will accept a date like 2020-09-10 or datetime(2020, 9, 10)
- Using from datetime import datetime
- xmin=datetime(2020, 9, 10), xmax=datetime(2020, 9, 10) + timedelta(days=3)
- Given date = df.index[9], xmin=date, xmax=date + pd.Timedelta(days=3), where the index is a DatetimeIndex.
The date column on the axis must be a datetime dtype. If using pandas, then use pd.to_datetime. For an array or list, refer to Converting numpy array of strings to datetime or Convert datetime list into date python, respectively.

import pandas_datareader as web  # conda or pip install this; not part of pandas
import pandas as pd
import matplotlib.pyplot as plt

# get test data; the Date index is already downloaded as datetime dtype
df = web.DataReader(^gspc, data_source=yahoo, start=2020-09-01, end=2020-09-28).iloc[:, :2]

# display(df.head(2))
                   High          Low
Date                                
2020-09-01  3528.030029  3494.600098
2020-09-02  3588.110107  3535.229980

# plot dataframe
ax = df.plot(figsize=(9, 6), title=S&P 500, ylabel=Price)

# add horizontal line
ax.hlines(y=3450, xmin=2020-09-10, xmax=2020-09-17, color=purple, label=test)

ax.legend()
plt.show()

Sample time series data if web.DataReader doesnt work.

data = {pd.Timestamp(2020-09-01 00:00:00): {High: 3528.03, Low: 3494.6}, pd.Timestamp(2020-09-02 00:00:00): {High: 3588.11, Low: 3535.23}, pd.Timestamp(2020-09-03 00:00:00): {High: 3564.85, Low: 3427.41}, pd.Timestamp(2020-09-04 00:00:00): {High: 3479.15, Low: 3349.63}, pd.Timestamp(2020-09-08 00:00:00): {High: 3379.97, Low: 3329.27}, pd.Timestamp(2020-09-09 00:00:00): {High: 3424.77, Low: 3366.84}, pd.Timestamp(2020-09-10 00:00:00): {High: 3425.55, Low: 3329.25}, pd.Timestamp(2020-09-11 00:00:00): {High: 3368.95, Low: 3310.47}, pd.Timestamp(2020-09-14 00:00:00): {High: 3402.93, Low: 3363.56}, pd.Timestamp(2020-09-15 00:00:00): {High: 3419.48, Low: 3389.25}, pd.Timestamp(2020-09-16 00:00:00): {High: 3428.92, Low: 3384.45}, pd.Timestamp(2020-09-17 00:00:00): {High: 3375.17, Low: 3328.82}, pd.Timestamp(2020-09-18 00:00:00): {High: 3362.27, Low: 3292.4}, pd.Timestamp(2020-09-21 00:00:00): {High: 3285.57, Low: 3229.1}, pd.Timestamp(2020-09-22 00:00:00): {High: 3320.31, Low: 3270.95}, pd.Timestamp(2020-09-23 00:00:00): {High: 3323.35, Low: 3232.57}, pd.Timestamp(2020-09-24 00:00:00): {High: 3278.7, Low: 3209.45}, pd.Timestamp(2020-09-25 00:00:00): {High: 3306.88, Low: 3228.44}, pd.Timestamp(2020-09-28 00:00:00): {High: 3360.74, Low: 3332.91}}

df = pd.DataFrame.from_dict(data, index)

Barplot and Histograms

Note that barplots are usually 0 indexed, regardless of the axis labels, so select xmin and xmax based on the bar index, not the tick label.
- ax.get_xticklabels() will show the locations and labels.

import pandas as pd
import seaborn as sns  # for tips data

# load data
tips = sns.load_dataset(tips)

# histogram
ax = tips.plot(kind=hist, y=total_bill, bins=30, ec=k, title=Histogram with Horizontal Line)
_ = ax.hlines(y=6, xmin=0, xmax=55, colors=r)

# barplot 
ax = tips.loc[5:25, [total_bill, tip]].plot(kind=bar, figsize=(15, 4), title=Barplot with Vertical Lines, rot=0)
_ = ax.hlines(y=6, xmin=3, xmax=15, colors=r)