I'm trying to edit a figure that was obtained using an external function.
For example, "nolds.lyap_r" function creates a figure. Let's say I want to add a title to it after it was plotted. How can I do it?
import nolds
import numpy as np
import matplotlib.pyplot as plt
nolds.lyap_r(y, debug_plot=True)
I guess I need to use plt.gca() or plt.gcf() but it didn't work for me:
ax=plt.gca()
ax.set_title("ABC")
pyplot.draw() is there to update the existing figure:
plt.title('A good title')
plt.draw()
Related
In the table below, I have values and frequencies. I'd like to draw a box-plot using Jupyter Notebook. I googled it but not able to find any answers.
My idea is to create a column, 2,2,2,2,4,4,4,4,4,4,4,...
But I think there must be a better way.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
value=np.array([2,4,6,7,10])
freq=np.array([4,7,8,5,2])
# do something here
plt.boxplot(newdata)
plt.show()
use numpy's repeat:
newdata = np.repeat(value,freq)
I'm generating a heatmap from a pandas dataframe using a code that looks like this on my apple computer.
import matplotlib.pyplot as plt
import seaborn as sns
fig, ax = plt.subplots(figsize=(14,14))
sns.set(font_scale=1.4)
sns_plot = sns.heatmap(df, annot=True, linewidths=.5, fmt='g', ax=ax).set_yticklabels(ax.get_yticklabels(), rotation=0)
ax.set_ylabel('Product')
ax.set_xlabel('Manufacturer')
ax.xaxis.set_ticks_position('top')
ax.xaxis.set_label_position('top')
fig.savefig('output.png')
And I get a heatmap looking like this:
I then put my code in a docker container with an ubuntu image and I install the same version of seaborn. The only difference is that I need to add a matplotlib configuration so that TCL doesn't scream:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
And I get a heatmap that looks like this (I use the same code and the same pandas dataframe):
I'm unable to find why the color gradient is inverted and would love to hear if you have any idea.
Thank you !
The default colormap has changed to 'rocket' for sequential data with 0.8 release of seaborn, see the release notes. The colormap looks this way now:
You can always use the cmap argument and specify which colormap you prefer to use. For example, to get the pre-0.8 colormap for non-divergent data use: cmap=sns.cubehelix_palette(light=.95, as_cmap=True).
I run a several code and get
Draw = pf.plot_drawdown_periods(returns, top=5).set_xlabel('Date')
type(Draw)
<matplotlib.text.Text at 0x7fb063733f90>
How can make my result visible in different ways?
You need to explicitly call pyplot.show() to display the graphics.
import matplotlib.pyplot as plt
pf.plot_drawdown_periods(returns, top=5).set_xlabel('Date')
plt.show()
I am interested in using the interact function to use a slider to adjust the position of text in a matplotlib plot (you know, instead of adjusting the position, running the code, and repeating 1000 times).
Here's a simple example of a plot
import matplotlib.pyplot as plt
x=0.2
y=0.9
plt.text(x, y,'To move',size=19)
plt.show()
and some interact code
from __future__ import print_function
from ipywidgets import interact, interactive, fixed
import ipywidgets as widgets
def f(x):
return x
interact(f, cx=0.2)
I'm wondering how I can combine these to generate a plot with the text along with a slider that will interactively move the text based on the specified value for x. Is this possible? What if I want to do the same for y?
Thanks in advance!
Here you go:
%matplotlib inline
import matplotlib.pyplot as plt
from ipywidgets import interact
def do_plot(x=0.2, y=0.9):
plt.text(x, y,'To move',size=19)
plt.show()
interact(do_plot)
I want the text to appear beside the box instead of inside it:
Here is what I did:
import matplotlib as mpl
import matplotlib.pyplot as plt
from custombox import MyStyle
fig = plt.figure(figsize=(10,10))
legend_ax = plt.subplot(111)
legend_ax.annotate("Text",xy=(0.5,0.5),xycoords='data',xytext=(0.5, 0.5),textcoords= ('data'),ha="center",rotation = 180,bbox=dict(boxstyle="angled, pad=0.5", fc='white', lw=4, ec='Black'))
legend_ax.text(0.6,0.5,"Text", ha="center",size=15)
Here is what it gives me:
Note: custombox is similar to the file that is written in this link:
http://matplotlib.org/1.3.1/users/annotations_guide.html
My ultimate aim is to make it look legend like where the symbol (angled box) appears beside the text that represents it.
EDIT 1: As suggested by Ajean I have annotated text separately but I can't turn of the text within the arrow
One way to do it would be to separate the text and the bbox (which you can reproduce using an arrow). The following gives me something close to what you want, I think.
import matplotlib.pyplot as plt
from matplotlib import patches
fig = plt.figure(figsize=(5,5))
ax = fig.add_subplot(111)
ax.annotate("Text", (0.4,0.5))
bb = patches.FancyArrow(0.5,0.5,0.1,0.0,length_includes_head=True, width=0.05,
head_length=0.03, head_width=0.05, fc='white', ec='black',
lw=4)
ax.add_artist(bb)
plt.show()
You can futz with the exact placement as needed. I'm not an expert on all the kwargs, so this may not be the best solution, but it will work.