Believe it or not I need help with formatting the title of the legend (not the title of the plot) in a simple plot. I am plotting two series of data (X1 and X2) against Y in a twiny() plot.
I call matplotlib.lines to construct lines for the legend and then call plt.legend to construct a legend pass text strings to name/explain the lines, format that text and place the legend. I could also pass a title-string to plt.legend but I cannot format it.
The closest I have come to a solution is to create another 'artist' for the title using .legend()set_title and then format the title text. I assign it to a variable and call the variable in the above mentioned plt.legend. This does not result in an error nor does it produce the desired effect. I have no control over the placement of the title.
I have read through a number of S-O postings and answers on legend-related issues, looked at the MPL docs, various tutorial type web-pages and even taken a peak at a GIT-hub issue (#10391). Presumably the answer to my question is somewhere in there but not in a format that I have been able to successfully implement.
#Imports
import matplotlib.pyplot as plt
import matplotlib.lines as mlines
import numpy as np
import seaborn as sns
plt.style.use('seaborn')
#Some made up data
y = np.arange(0, 1200, 100)
x1 = (np.log(y+1))
x2 = (2.2*x1)
#Plot figure
fig = plt.figure(figsize = (12, 14))
fig = plt.figure()
ax1 = fig.add_subplot(111)
ax2 = ax1.twiny()
sy1, sy2 = 'b-', 'r-'
tp, bm = 0, 1100
red_ticks = np.arange(0, 11, 2)
ax1.plot(x1, y, sy1)
ax1.set_ylim(tp, bm)
ax1.set_xlim(0, 10)
ax1.set_ylabel('Distance (m)')
ax1.set_xlabel('Area')
ax1.set_xticks(red_ticks)
blue_ticks = np.arange(0, 22, 4)
ax2.plot(x2, y, sy2)
ax2.set_xlim(0, 20)
ax2.set_xlabel('Volume')
ax2.set_xticks(blue_ticks)
ax2.grid(False)
x1_line = mlines.Line2D([], [], color='blue')
x2_line = mlines.Line2D([], [], color='red')
leg = ax1.legend().set_title('Format Legend Title ?',
prop = {'size': 'large',
'family':'serif',
'style':'italic'})
plt.legend([x1_line, x2_line], ['Blue Model', 'Red Model'],
title = leg,
prop ={'size':12,
'family':'serif',
'style':'italic'},
bbox_to_anchor = (.32, .92))
So what I want is a simple way to control the formatting of both the legend-title and legend-text in a single artist, and also have control over the placement of said legend.
The above code returns a "No handles with labels found to put in legend."
You need one single legend. You can set the title of that legend (not some other legend); then style it to your liking.
leg = ax2.legend([x1_line, x2_line], ['Blue Model', 'Red Model'],
prop ={'size':12, 'family':'serif', 'style':'italic'},
bbox_to_anchor = (.32, .92))
leg.set_title('Format Legend Title ?', prop = {'size': 24, 'family':'sans-serif'})
Unrelated, but also important: Note that you have two figures in your code. You should remove one of them.
Related
With this code:
from pandas_datareader import data as web
import pandas as pd
import datetime
df = web.DataReader('fb', 'yahoo', start = datetime.date(2022,5,28), end = datetime.datetime.now())
df['pct'] = df.Close.pct_change()
plt.style.use('fivethirtyeight')
plt.rcParams['font.family'] = 'Serif'
fig, ax = plt.subplots()
ax2 = ax.twinx()
plt.axis('off')
df.plot.bar(y = 'pct', ax = ax, grid = True, color = '#bf3c3d')
ax.set_title('Large Title',loc='left', fontname="Times New Roman", size=28,fontweight="bold")
ax.set(xlabel=None)
ax.text(0, 0.07, '\nAttention Catcher', fontsize=13, ha='left')
ax.get_legend().remove()
plt.grid(color = 'green', linestyle = 'dotted', linewidth = 0.5)
This plot is produced:
The issue which I am running into is that I want the text "Attention Catcher" to be lined by exactly on the line where "Large Title" started.
However when the date is changed to produces more bars, the text shifts. So the x,y values of text are dependent on the plot.
What can I do for the text to remain lined up with "Large Title"
I would like it to look like this regardless of the number of bars being plotted. Please help.
By selecting the coordinate system in the string annotation, it can be set to be fixed, independent of the graph size. The value you set was set manually and should be modified.
ax.text(0, 0.07, '\nAttention Catcher', fontsize=13, ha='left')
Change to the following
ax.text(0.08, 1.07, '\nAttention Catcher', ha='left', va='top', fontsize=13, transform=fig.transFigure)
If the subject period is short
So currently learning how to import data and work with it in matplotlib and I am having trouble even tho I have the exact code from the book.
This is what the plot looks like, but my question is how can I get it where there is no white space between the start and the end of the x-axis.
Here is the code:
import csv
from matplotlib import pyplot as plt
from datetime import datetime
# Get dates and high temperatures from file.
filename = 'sitka_weather_07-2014.csv'
with open(filename) as f:
reader = csv.reader(f)
header_row = next(reader)
#for index, column_header in enumerate(header_row):
#print(index, column_header)
dates, highs = [], []
for row in reader:
current_date = datetime.strptime(row[0], "%Y-%m-%d")
dates.append(current_date)
high = int(row[1])
highs.append(high)
# Plot data.
fig = plt.figure(dpi=128, figsize=(10,6))
plt.plot(dates, highs, c='red')
# Format plot.
plt.title("Daily high temperatures, July 2014", fontsize=24)
plt.xlabel('', fontsize=16)
fig.autofmt_xdate()
plt.ylabel("Temperature (F)", fontsize=16)
plt.tick_params(axis='both', which='major', labelsize=16)
plt.show()
There is an automatic margin set at the edges, which ensures the data to be nicely fitting within the axis spines. In this case such a margin is probably desired on the y axis. By default it is set to 0.05 in units of axis span.
To set the margin to 0 on the x axis, use
plt.margins(x=0)
or
ax.margins(x=0)
depending on the context. Also see the documentation.
In case you want to get rid of the margin in the whole script, you can use
plt.rcParams['axes.xmargin'] = 0
at the beginning of your script (same for y of course). If you want to get rid of the margin entirely and forever, you might want to change the according line in the matplotlib rc file:
axes.xmargin : 0
axes.ymargin : 0
Example
import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset('tips')
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4))
tips.plot(ax=ax1, title='Default Margin')
tips.plot(ax=ax2, title='Margins: x=0')
ax2.margins(x=0)
Alternatively, use plt.xlim(..) or ax.set_xlim(..) to manually set the limits of the axes such that there is no white space left.
If you only want to remove the margin on one side but not the other, e.g. remove the margin from the right but not from the left, you can use set_xlim() on a matplotlib axes object.
import seaborn as sns
import matplotlib.pyplot as plt
import math
max_x_value = 100
x_values = [i for i in range (1, max_x_value + 1)]
y_values = [math.log(i) for i in x_values]
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4))
sn.lineplot(ax=ax1, x=x_values, y=y_values)
sn.lineplot(ax=ax2, x=x_values, y=y_values)
ax2.set_xlim(-5, max_x_value) # tune the -5 to your needs
I have a simple matplotlib line chart displaying four timeseries. What I'd like to do is annotate it in two ways:
Change the background color of a region of the plot where there's a different regime, e.g. high volatility period has a light blue rectangle behind the plot
add a green up arrow and a red down arrow at key points in the graph (showing where orders are placed)
I think I know how to add the arrows (see below) but have no idea how to do the "on/off" regions. Any recommendations?
plt.plot(datetime.datetime(2020, 9, 13, 5, 0, 0), 10400, marker=r'$\uparrow$')
As mentioned in the comments, you can use ax.axhspan() and ax.axvspan() to add color to a specific background range. Arrows are set with ax.arrow(x,y,dx,dy), which draws an arrow alone. The sample solution is a customized version of the official reference. matplotlib.axes.Axes.arrow
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.cbook as cbook
years = mdates.YearLocator() # every year
months = mdates.MonthLocator() # every month
years_fmt = mdates.DateFormatter('%Y')
data = cbook.get_sample_data('goog.npz', np_load=True)['price_data']
fig, ax = plt.subplots(figsize=(12,9))
ax.plot('date', 'adj_close', data=data, color='g', lw=2.0)
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(years_fmt)
ax.xaxis.set_minor_locator(months)
datemin = np.datetime64(data['date'][0], 'Y')
datemax = np.datetime64(data['date'][-1], 'Y') + np.timedelta64(1, 'Y')
ax.set_xlim(datemin, datemax)
ax.format_xdata = mdates.DateFormatter('%Y-%m-%d')
ax.format_ydata = lambda x: '$%1.2f' % x # format the price.
# update
ax.axvspan(13514,13879, color='skyblue', alpha=0.2)
ax.arrow(13650,550,55,55, zorder=10, width=10, fc='b', ec='b')
ax.arrow(13930,630,25,-55, zorder=10, width=10, fc='red',ec='red')
fig.autofmt_xdate()
plt.show()
I would like to generate a centered figure legend for subplot(s), for which there is a single label. For my actual use case, the number of subplot(s) is greater than or equal to one; it's possible to have a 2x2 grid of subplots and I would like to use the figure-legend instead of using ax.legend(...) since the same single label entry will apply to each/every subplot.
As a brief and simplified example, consider the code just below:
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.sin(x)
fig, ax = plt.subplots()
ax.plot(x, y, color='orange', label='$f(x) = sin(x)$')
fig.subplots_adjust(bottom=0.15)
fig.legend(mode='expand', loc='lower center')
plt.show()
plt.close(fig)
This code will generate the figure seen below:
I would like to use the mode='expand' kwarg to make the legend span the entire width of the subplot(s); however, doing so prevents the label from being centered. As an example, removing this kwarg from the code outputs the following figure.
Is there a way to use both mode='expand' and also have the label be centered (since there is only one label)?
EDIT:
I've tried using the bbox_to_anchor kwargs (as suggested in the docs) as an alternative to mode='expand', but this doesn't work either. One can switch out the fig.legend(...) line for the line below to test for yourself.
fig.legend(loc='lower center', bbox_to_anchor=(0, 0, 1, 0.5))
The handles and labels are flush against the left side of the legend. There is no mechanism to allow for aligning them.
A workaround could be to use 3 columns of legend handles and fill the first and third with a transparent handle.
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.sin(x)
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.15)
line, = ax.plot(x, y, color='orange', label='$f(x) = sin(x)$')
proxy = plt.Rectangle((0,0),1,1, alpha=0)
fig.legend(handles=[proxy, line, proxy], mode='expand', loc='lower center', ncol=3)
plt.show()
I'm facing a problem in showing the legend in the correct format using matplotlib.
EDIT: I have 4 subplots in a figure in 2 by 2 format and I want legend only on the first subplot which has two lines plotted on it. The legend that I got using the code attached below contained endless entries and extended vertically throughout the figure. When I use the same code using linspace to generate fake data the legend works absolutely fine.
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick
import os
#------------------set default directory, import data and create column output vectors---------------------------#
path="C:/Users/Pacman/Data files"
os.chdir(path)
data =np.genfromtxt('vrp.txt')
x=np.array([data[:,][:,0]])
y1=np.array([data[:,][:,6]])
y2=np.array([data[:,][:,7]])
y3=np.array([data[:,][:,9]])
y4=np.array([data[:,][:,11]])
y5=np.array([data[:,][:,10]])
nrows=2
ncols=2
tick_l=6 #length of ticks
fs_axis=16 #font size of axis labels
plt.rcParams['axes.linewidth'] = 2 #Sets global line width of all the axis
plt.rcParams['xtick.labelsize']=14 #Sets global font size for x-axis labels
plt.rcParams['ytick.labelsize']=14 #Sets global font size for y-axis labels
plt.subplot(nrows, ncols, 1)
ax=plt.subplot(nrows, ncols, 1)
l1=plt.plot(x, y2, 'yo',label='Flow rate-fan')
l2=plt.plot(x,y3,'ro',label='Flow rate-discharge')
plt.title('(a)')
plt.ylabel('Flow rate ($m^3 s^{-1}$)',fontsize=fs_axis)
plt.xlabel('Rupture Position (ft)',fontsize=fs_axis)
# This part is not working
plt.legend(loc='upper right', fontsize='x-large')
#Same code for rest of the subplots
I tried to implement a fix suggested in the following link, however, could not make it work:
how do I make a single legend for many subplots with matplotlib?
Any help in this regard will be highly appreciated.
If I understand correctly, you need to tell plt.legend what to put as legends... at this point it is being loaded empty. What you get must be from another source. I have quickly the following, and of course when I run fig.legend as you do I get nothing.
import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure()
ax1 = fig.add_axes([0.1, 0.1, 0.4, 0.7])
ax2 = fig.add_axes([0.55, 0.1, 0.4, 0.7])
x = np.arange(0.0, 2.0, 0.02)
y1 = np.sin(2*np.pi*x)
y2 = np.exp(-x)
l1, l2 = ax1.plot(x, y1, 'rs-', x, y2, 'go')
y3 = np.sin(4*np.pi*x)
y4 = np.exp(-2*x)
l3, l4 = ax2.plot(x, y3, 'yd-', x, y4, 'k^')
fig.legend(loc='upper right', fontsize='x-large')
#fig.legend((l1, l2), ('Line 1', 'Line 2'), 'upper left')
#fig.legend((l3, l4), ('Line 3', 'Line 4'), 'upper right')
plt.show()
I'd suggest doing one by one, and then applying for all.
It is useful to work with the axes directly (ax in your case) when when working with subplots. So if you set up two plots in a figure and only wish to have a legend in your second plot:
t = np.linspace(0, 10, 100)
plt.figure()
ax1 = plt.subplot(2, 1, 1)
ax1.plot(t, t * t)
ax2 = plt.subplot(2, 1, 2)
ax2.plot(t, t * t * t)
ax2.legend('Cubic Function')
Note that when creating the legend, I am doing so on ax2 as opposed to plt. If you wish to create a second legend for the first subplot, you can do so in the same way but on ax1.