CODEWITHSUNDEEP
pythonjupyter-notebookseaborn
Lexicon
Lexicon

Reputation: 2625

Can't create unnormalized histogram using seaborn with full values represented in plot

I have a CSV file named data.csv that has three columns:

vendor,sample
A,3
A,2
B,1
A,1
....

I'd like to take everything that has the first column = A and create a histogram in seaborn that shows the number of occurrences that a sample shows up. don't want the data to be normalized. When I attempt to plot this, the y-axis is much smaller than the actual value. for example, in the code below, there are 708 occurrences of "1" but in the histogram, 1 only goes up to 30 on the y-axis. 

data = pd.read_csv(r'C:\data\data.csv')
v1=list(data[data['Vendor'] == 'A']['Sample'])
print(str(v1))


sns.distplot(v1,norm_hist=False)
count=0
for i in v1:
    if i == 1:
        count = count+1
print(str(count))

Output:

[3, 2, 1, 1, 1, 2, 2, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1,1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 1, 1, 1, 1, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 1, 1, 1, 1, 1, 1, 6, 2, 2, 2, 2, 1, 1, 1, 1, 1, 3, 4, 3, 1, 1, 2, 2, 2, 3, 3, 3, 3, 3, 2, 2, 2, 3, 3, 3, 2, 3, 3, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 3, 2, 2, 3, 3, 2, 3, 3, 1, 2, 3, 2, 3, 3, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 3, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 3, 3, 3, 3, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 4, 4, 3, 3, 4, 3, 3, 3, 3, 3, 3, 2, 1, 2, 4, 3, 3, 1, 1, 1, 1, 1, 1, 3, 3, 1, 2, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 3, 3, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 2, 1, 3, 3, 3, 3, 3, 3, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 8, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 2, 1, 3, 1, 3, 3, 3, 1, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 6, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 1, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 2, 3, 3, 3, 3, 3, 2, 3, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 3, 3, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 2, 1, 3, 1, 1, 2, 2, 2, 1, 2, 2, 2, 2, 4, 1, 1, 3, 3, 3, 3, 3, 6, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 3, 3, 3, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 3, 1, 1, 1, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 2, 2, 2, 6, 3, 3, 3, 3, 6, 1, 1, 1, 3, 3, 3]
708

output

I'd like the histogram to correctly represent the number of occurences for each sample value for vendor "A" and well as the numerical value above the bar.

Upvotes: 0

Views: 174

Answers (1)

JohanC
JohanC

Reputation: 80459

distplot has a parameter kde which is default True. It is meant to draw a "kernel density estimation" over the histogram. This only can be drawn together well with the histogram if both are normalized. Such a kde tries to mimic the underlying probability distribution function (pdf). This is not meaningful for discrete distributions. To have a non-normalized distplot, the parameter kde=False should be set explicitly.

To annotate the heights of the bars, one can loop through the generated patches, get their height, their position and their width to put a text at the appropriate position. Adding '\n' to the string puts the text with a nice little padding just above the bar.

import matplotlib.pyplot as plt
import seaborn as sns

# v1 = [3,2,1,1,1,2,2,2,2,1,2,2,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,1,...]
plot = sns.distplot(v1, kde=False)
for bar in plot.patches:
    h = bar.get_height()
    if h != 0:
        plot.text(bar.get_x() + bar.get_width() / 2,
                  h,
                  f'{h:.0f}\n',
                  ha='center',
                  va='center')
plt.show()

demo plot

Upvotes: 1

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