Histogramme

Jens Wagner 07/2015

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Download histogramm.txt

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.mlab as mlab
%matplotlib inline

data=np.genfromtxt('data/histogramm.txt')  #Hier der Pfad zu Euren Daten eintragen

print(data[:5])

[ 44.14166  48.02898  49.55642  44.14077  42.09511]

plt.hist(data)
plt.xlabel('x / unit')
plt.ylabel('y / unit')

<matplotlib.text.Text at 0x708c6d8>

plt.hist(data, bins=30) #Zahl der bins auf 30 setzen
plt.xlabel('x / unit')
plt.ylabel('y / unit')

<matplotlib.text.Text at 0x7375eb8>

plt.hist(data, bins=30, normed=True) #Normierung, Fläche des Histogramms=1
plt.xlabel('x / unit')
plt.ylabel('y / unit')

<matplotlib.text.Text at 0x7379470>

#Kummulative Verteiling
plt.hist(data, bins=30, normed=True, cumulative=True)
plt.xlabel('x / unit')
plt.ylabel('y / unit')

<matplotlib.text.Text at 0x7500cf8>

#Mittelwert, Standardabweichung der Verteilung
mean=np.mean(data)
std_dev=np.std(data)
print(mean)

44.8045123731

n, bins, patches=plt.hist(data, bins=30, normed=True)

#Gausskurve in das Histogramm zeichnen
gauss = mlab.normpdf(bins, mean, std_dev)
plt.plot(bins, gauss, 'k', linewidth=2)

[<matplotlib.lines.Line2D at 0x75f4eb8>]