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Closed 4 months ago.
I am making a histogram using matplotlib. I am using integer data and I want them to represent 1 bin. The following is the sample code which I made.
import matplotlib.pyplot as plt
a=[1,2,2,3,3,3,4,4,4,4]
plt.figure()
plt.hist(a,bins=4)
plt.show()
The histogram which I got is above. This have left end 1 ad rightend 4. I want the width of the histogram to be 1, however, this will just show 0.75 size. Moreover, I want the x value to locate at the center of the bar of histogram. Is there any way I can adjust?
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I'd like to construct a univariate KDE plot using Seaborn. The x-axis is amygdala volume, and I would like the y-axis to display probability densities. But when I use seaborn's kdeplot method, it seems like it's returning the raw counts (as if it was a histogram) instead of the densities. How do I get it to show the densities?
I've tried looking for parameters to include, but nothing would help.
plt.figure(figsize=(15,8))
sns.kdeplot(data=n90pol, x='amygdala', bw_adjust=0.5)
plt.xlabel('Amygdala Volume', fontsize=16);
plt.ylabel('Density', fontsize=16);
plt.title('KDE plot of Amygdala Volume', fontsize=24)
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There are a few examples showing how to use "shrink" for changing the colorbar. How can I automatically figure out what the shrink should be so the colorbar is equal to the height of the heatmap?
I don't have a matplotlib axis because I am using seaborn and plotting the heatmap from the dataframe.
r = []
r.append(np.arange(0,1,.1))
r.append(np.arange(0,1,.1))
r.append(np.arange(0,1,.1))
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I have been trying to get a bar plot with value labels on each bar. I have searched all over but can't get this done. My df is the one below.
Pillar %
Exercise 19.4
Meaningful Activity 19.4
Sleep 7.7
Nutrition 22.9
Community 16.2
Stress Management 23.9
My code so far is
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plt.show()
Use ax.bar_label:
ax = df.plot(x='Pillar', y='%', kind='bar', legend=False, rot=0)
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I want to draw a line on y=0. However, I am not sure how to do that using pandas built-in charting.
df.mean(axis=1).plot() I am running this and that is the result.
Catch the ax instance returned by plot, and you can use axhline:
ax = df.mean(axis=1).plot()
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Output:
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Getting legend in seaborn jointplot
(2 answers)
Closed 3 years ago.
When generating bivariate plots like hexbin, pandas generates a legend explaining frequency value for each color shade:
pokemon.plot.hexbin(x='HP', y='Attack', gridsize=30)
I cannot find a similar way to generate such a legend for jointplot and kdeplot in seaborn:
sns.jointplot(data=pokemon, x='HP', y='Attack', kind='hex')
sns.kdeplot(pokemon['HP'], pokemon['Attack'], shade=True)
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for a kdeplot, simply pass cbar=True
cbar : bool, optional
If True and drawing a bivariate KDE plot, add a colorbar.