How to create histogram with multiple arrays with various length, with percentage on y axes with matplotlib
1
I would like to create histogram plot for multiple arrays, that will have shared percentage y-axis.
For example, this plot correctly:
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.ticker as ticker
# these are my measurements, unsorted
num_of_points = 10000
num_of_bins = 20
data = np.random.randn(num_of_points) # generate random numbers from a gaussian distribution
fig, ax = plt.subplots()
ax.hist(data, bins=num_of_bins, edgecolor='black', alpha=0.3)
ax.set_title("Histogram")
ax.set_xlabel("X axis")
ax.set_ylabel("Percentage")
ax.yaxis.set_major_formatter(ticker.PercentFormatter(xmax=len(data)))
plt.show()
Figure 1
But when I add another data with diffrent lenght, percentage for data2 is off, because PercentFormatter takes len(data).
num_of_points = 10000
num_of_points2 = 30000
num_of_bins = 20
data = np.random.randn(num_of_points) # generate random numbers from a gaussian distribution
data2 = np.random.randn(num_of_points2)
fig, ax = plt.subplots()
ax.hist(data, bins=num_of_bins, edgecolor='black', alpha=0.3)
ax.hist(data2, bins=num_of_bins, edgecolor='black', alpha=0.3)
ax.set_title("Histogram")
ax.set_xlabel("X axis")
ax.set_ylabel("Percentage")
ax.yaxis.set_major_formatter(ticker.PercentFormatter(xmax=len(data2)))
plt.show()
Figure 2
So how can I have shared percentage y-ax, that will be correct for both data arrays?
python matplotlib
asked Nov 13 '18 at 9:33
SimonSimon
64
add a comment |
1
I would like to create histogram plot for multiple arrays, that will have shared percentage y-axis.
For example, this plot correctly:
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.ticker as ticker
# these are my measurements, unsorted
num_of_points = 10000
num_of_bins = 20
data = np.random.randn(num_of_points) # generate random numbers from a gaussian distribution
fig, ax = plt.subplots()
ax.hist(data, bins=num_of_bins, edgecolor='black', alpha=0.3)
ax.set_title("Histogram")
ax.set_xlabel("X axis")
ax.set_ylabel("Percentage")
ax.yaxis.set_major_formatter(ticker.PercentFormatter(xmax=len(data)))
plt.show()
Figure 1
But when I add another data with diffrent lenght, percentage for data2 is off, because PercentFormatter takes len(data).
num_of_points = 10000
num_of_points2 = 30000
num_of_bins = 20
data = np.random.randn(num_of_points) # generate random numbers from a gaussian distribution
data2 = np.random.randn(num_of_points2)
fig, ax = plt.subplots()
ax.hist(data, bins=num_of_bins, edgecolor='black', alpha=0.3)
ax.hist(data2, bins=num_of_bins, edgecolor='black', alpha=0.3)
ax.set_title("Histogram")
ax.set_xlabel("X axis")
ax.set_ylabel("Percentage")
ax.yaxis.set_major_formatter(ticker.PercentFormatter(xmax=len(data2)))
plt.show()
Figure 2
So how can I have shared percentage y-ax, that will be correct for both data arrays?
python matplotlib
asked Nov 13 '18 at 9:33
SimonSimon
64
1
You need to rescale the distributions so to give each distribution an equal (overall) area on the graph. One way is by producing a probability density. Check out thedensityargument inplt.hist.
– Bonlenfum
Nov 13 '18 at 9:48
add a comment |
1
1
1
1
I would like to create histogram plot for multiple arrays, that will have shared percentage y-axis.
For example, this plot correctly:
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.ticker as ticker
# these are my measurements, unsorted
num_of_points = 10000
num_of_bins = 20
data = np.random.randn(num_of_points) # generate random numbers from a gaussian distribution
fig, ax = plt.subplots()
ax.hist(data, bins=num_of_bins, edgecolor='black', alpha=0.3)
ax.set_title("Histogram")
ax.set_xlabel("X axis")
ax.set_ylabel("Percentage")
ax.yaxis.set_major_formatter(ticker.PercentFormatter(xmax=len(data)))
plt.show()
Figure 1
But when I add another data with diffrent lenght, percentage for data2 is off, because PercentFormatter takes len(data).
num_of_points = 10000
num_of_points2 = 30000
num_of_bins = 20
data = np.random.randn(num_of_points) # generate random numbers from a gaussian distribution
data2 = np.random.randn(num_of_points2)
fig, ax = plt.subplots()
ax.hist(data, bins=num_of_bins, edgecolor='black', alpha=0.3)
ax.hist(data2, bins=num_of_bins, edgecolor='black', alpha=0.3)
ax.set_title("Histogram")
ax.set_xlabel("X axis")
ax.set_ylabel("Percentage")
ax.yaxis.set_major_formatter(ticker.PercentFormatter(xmax=len(data2)))
plt.show()
Figure 2
So how can I have shared percentage y-ax, that will be correct for both data arrays?
python matplotlib
asked Nov 13 '18 at 9:33
SimonSimon
64
I would like to create histogram plot for multiple arrays, that will have shared percentage y-axis.
For example, this plot correctly:
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.ticker as ticker
# these are my measurements, unsorted
num_of_points = 10000
num_of_bins = 20
data = np.random.randn(num_of_points) # generate random numbers from a gaussian distribution
fig, ax = plt.subplots()
ax.hist(data, bins=num_of_bins, edgecolor='black', alpha=0.3)
ax.set_title("Histogram")
ax.set_xlabel("X axis")
ax.set_ylabel("Percentage")
ax.yaxis.set_major_formatter(ticker.PercentFormatter(xmax=len(data)))
plt.show()
Figure 1
But when I add another data with diffrent lenght, percentage for data2 is off, because PercentFormatter takes len(data).
num_of_points = 10000
num_of_points2 = 30000
num_of_bins = 20
data = np.random.randn(num_of_points) # generate random numbers from a gaussian distribution
data2 = np.random.randn(num_of_points2)
fig, ax = plt.subplots()
ax.hist(data, bins=num_of_bins, edgecolor='black', alpha=0.3)
ax.hist(data2, bins=num_of_bins, edgecolor='black', alpha=0.3)
ax.set_title("Histogram")
ax.set_xlabel("X axis")
ax.set_ylabel("Percentage")
ax.yaxis.set_major_formatter(ticker.PercentFormatter(xmax=len(data2)))
plt.show()
Figure 2
So how can I have shared percentage y-ax, that will be correct for both data arrays?
python matplotlib
python matplotlib
asked Nov 13 '18 at 9:33
SimonSimon
64
asked Nov 13 '18 at 9:33
SimonSimon
64
asked Nov 13 '18 at 9:33
SimonSimon
64
asked Nov 13 '18 at 9:33
SimonSimon
64
asked Nov 13 '18 at 9:33
SimonSimon
64
64
1
You need to rescale the distributions so to give each distribution an equal (overall) area on the graph. One way is by producing a probability density. Check out thedensityargument inplt.hist.
– Bonlenfum
Nov 13 '18 at 9:48
add a comment |
1
You need to rescale the distributions so to give each distribution an equal (overall) area on the graph. One way is by producing a probability density. Check out thedensityargument inplt.hist.
– Bonlenfum
Nov 13 '18 at 9:48
1
1
You need to rescale the distributions so to give each distribution an equal (overall) area on the graph. One way is by producing a probability density. Check out the
density argument in plt.hist.– Bonlenfum
Nov 13 '18 at 9:48
You need to rescale the distributions so to give each distribution an equal (overall) area on the graph. One way is by producing a probability density. Check out the
density argument in plt.hist.– Bonlenfum
Nov 13 '18 at 9:48
add a comment |
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1
You need to rescale the distributions so to give each distribution an equal (overall) area on the graph. One way is by producing a probability density. Check out the
densityargument inplt.hist.– Bonlenfum
Nov 13 '18 at 9:48