I would like to add a figure description to the bottom of my group of subplots. Is there a built in way to do this or do I have to keep messing with text() to get it placed correctly
This will put the label centered and 15 pixels above the bottom of the figure.
import matplotlib.pyplot as plt
import matplotlib.transforms as mtrans
fig, ax = plt.subplots(2, 2)
trans = mtrans.blended_transform_factory(fig.transFigure,
mtrans.IdentityTransform())
txt = fig.text(.5, 15, "total label", ha='center')
txt.set_transform(trans)
See http://matplotlib.org/users/transforms_tutorial.html for more on how to work with transforms.
Related
I have a timeseries data timeseries.txt. First I select a index value (here 50) and put a red line mark on that selected index value. And I want to highlight portion before(idx-20) and after(idx+20) the red line index value on the timeseries.
I wrote this code however i am able to put the red line mark on the timeseries but while using fill_betweenx it doesnot work. I hope experts may help me overcoming this problem.Thanks.
import matplotlib.pyplot as plt
import numpy as np
input_data=np.loadtxt("timeseries.txt")
time=np.arange(len(input_data))
plt.plot(time,input_data)
idx = [50]
mark = [time[i] for i in idx]
plt.plot(idx,[input_data[i] for i in mark], marker="|",color='red',markerfacecolor='none',mew=0.4,ms=30,alpha=2.0)
plt.fill_betweenx(idx-20,idx+20 alpha=0.25,color='lightsteelblue')
plt.show()
If you are looking for just a semi-transparent rectangle, you can use patches.Rectangle to draw one. Refer here. I have updated your code to add a rectangle. See if this meets your requirement. I have used a sine wave as I didn't have your data.
import matplotlib.pyplot as plt
import numpy as np
## Create sine wave
x = np.arange(100)
input_data=np.sin(2*np.pi*3*x/100)
time=np.arange(len(input_data))
plt.plot(time,input_data)
idx = [50]
mark = [time[i] for i in idx]
plt.plot(idx,[input_data[i] for i in mark], marker="|", color='red', markerfacecolor='none', mew=0.4,ms=30,alpha=2.0)
#plt.fill_betweenx(mark,idx-20,0, alpha=0.25,color='lightsteelblue')
# Create a Rectangle patch
import matplotlib.patches as patches
from matplotlib.patches import Rectangle
plt.gca().add_patch(Rectangle((idx[0]-20, -0.15), 40, .3, facecolor = 'lightsteelblue',fill=True,alpha=0.25, lw=0))
plt.show()
EDIT
Please refer to the Rectangle documentation provided earlier in the response. You will need to adjust the start coordinates (x,y) and the height and width to see how big/small you need the Rectangle. For eg: changing the rectangle code like this...
plt.gca().add_patch(Rectangle((idx[0]-10, -0.40), 20, 0.8, facecolor = 'lightsteelblue',fill=True,alpha=0.25, lw=0))
will give you this plot.
I am using matplotlib to plot a pie chart. I have added a legend to the chart. However, i would like to add a "Total" to the legend, to sum up the values of all the other categories. Hence the value of "Total" would not be a part of the pie chart, and would only be shown in the legend. Is it possible for me to do that? Thank you.
You can create 2 legends. On the second one, you can create/manipulate symbol/text/title as you want. Here is a runnable code that you can try.
from matplotlib import pyplot as plt
import matplotlib.patches as mpatches
import numpy as np
fig = plt.figure()
ax = fig.add_axes([0,0,1,1])
ax.axis('equal')
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.pie(students, labels = langs,autopct='%1.2f%%')
# first legend
lgn = plt.legend()
ax = plt.gca().add_artist(lgn)
# second legend
gold_patch = mpatches.Patch(color='gold', label='Total= 9999') # use your description text here
second_legend = plt.legend(handles=[gold_patch], loc=1, \
bbox_to_anchor=(0.5, 0.35, 0.55, 0.35)) # adjust location of legend here
second_legend.set_frame_on(False) # use True/False as needed
second_legend.set_title("Other categories")
plt.show()
The output plot:
I created a scatter plot in seaborn using seaborn.relplot, but am having trouble putting the legend all in one graph.
When I do this simple way, everything works fine:
import pandas as pd
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
import seaborn as sns
df2 = df[df.ln_amt_000s < 700]
sns.relplot(x='ln_amt_000s', y='hud_med_fm_inc', hue='outcome', size='outcome', legend='brief', ax=ax, data=df2)
The result is a scatter plot as desired, with the legend on the right hand side.
However, when I try to generate a matplotlib figure and axes objects ahead of time to specify the figure dimensions I run into problems:
a4_dims = (10, 10) # generating a matplotlib figure and axes objects ahead of time to specify figure dimensions
df2 = df[df.ln_amt_000s < 700]
fig, ax = plt.subplots(figsize = a4_dims)
sns.relplot(x='ln_amt_000s', y='hud_med_fm_inc', hue='outcome', size='outcome', legend='brief', ax=ax, data=df2)
The result is two graphs -- one that has the scatter plots as expected but missing the legend, and another one below it that is all blank except for the legend on the right hand side.
How do I fix this such? My desired result is one graph where I can specify the figure dimensions and have the legend at the bottom in two rows, below the x-axis (if that is too difficult, or not supported, then the default legend position to the right on the same graph would work too)? I know the problem lies with "ax=ax", and in the way I am specifying the dimensions as matplotlib figure, but I'd like to know specifically why this causes a problem so I can learn from this.
Thank you for your time.
The issue is that sns.relplot is a "Figure-level interface for drawing relational plots onto a FacetGrid" (see the API page). With a simple sns.scatterplot (the default type of plot used by sns.relplot), your code works (changed to use reproducible data):
df = pd.read_csv("https://vincentarelbundock.github.io/Rdatasets/csv/datasets/iris.csv", index_col=0)
fig, ax = plt.subplots(figsize = (5,5))
sns.scatterplot(x = 'Sepal.Length', y = 'Sepal.Width',
hue = 'Species', legend = 'brief',
ax=ax, data = df)
plt.show()
Further edits to legend
Seaborn's legends are a bit finicky. Some tweaks you may want to employ:
Remove the default seaborn title, which is actually a legend entry, by getting and slicing the handles and labels
Set a new title that is actually a title
Move the location and make use of bbox_to_anchor to move outside the plot area (note that the bbox parameters need some tweaking depending on your plot size)
Specify the number of columns
fig, ax = plt.subplots(figsize = (5,5))
sns.scatterplot(x = 'Sepal.Length', y = 'Sepal.Width',
hue = 'Species', legend = 'brief',
ax=ax, data = df)
handles, labels = ax.get_legend_handles_labels()
ax.legend(handles=handles[1:], labels=labels[1:], loc=8,
ncol=2, bbox_to_anchor=[0.5,-.3,0,0])
plt.show()
I am trying to create a pie chart, as follows:
import matplotlib.pyplot as plt
import pandas as pd
# make a square figure and axes
plt.figure(1, figsize=(10,10))
plt.axes([0.01, 0.1, 0.6, 0.6])
# plt.style.use('fivethirtyeight')
# The slices will be ordered and plotted counter-clockwise.
labels = 'foo1', 'foo2', 'foo3', 'foo4'
fracs = pd.Series([10,30, 50,10],index=labels)
fracs.plot(kind='pie', labels=None, autopct='%1.0f%%')
plt.legend(bbox_to_anchor=(0.95, .9), loc=2, borderaxespad=0.,labels=labels)
plt.title('pie chart demo which should be center aligned not left', bbox={'facecolor':'0.8', 'pad':5})
plt.show()
Which is yeilding a piechart as:
But, I am facing two problem:
1) I dont like the color scheme. I would like a color scheme more inline with (I need 12 colors)
2) Titel is centered at the pie chart only. The legend is somehow out. I am trying to get the title centered over the chart and the legend.
Can someone kindly help?
I think that is a ggplot colorscheme that you are trying to emulate.
And your plt.axes command is what is displacing your chart to the left.
Try this:
import matplotlib.pyplot as plt
plt.style.use('ggplot')
plt.figure(1, figsize=(10,10))
labels = 'foo1', 'foo2', 'foo3', 'foo4'
sizes = [10,30, 50,10]
plt.pie(sizes, labels=labels)
plt.show()
I am trying to find a way to move the little multiplier below the x-axis to the top. I have a plot with two x-axis and the multiplier of the top axis is placed below the bottom x-axis, which I find confusing.
Here is a small example:
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
fig = plt.figure(num=None,figsize=(15, 2.5), dpi=300)
gs = mpl.gridspec.GridSpec(1,1)
ax2 = plt.subplot(gs[0,0])
ax1 = ax2.twiny()
ax1.grid(False)
ax1.set_xlim(0,10000000)
ax2.set_xlim(0,1000000)
ax1.set_ylim([0,100])
ax2.set_ylim([0,100])
plt.show()
Now, if you change ax2.set_xlim(0,1000000) to ax2.set_xlim(0,100000000), then both multipliers are placed below the bottom x-axis. Maybe it is also possible to prevent the multiplier from overlapping with the x-axis tick labels?
My problem with researching this is that I have no idea how this 'multiplier' is actually called.