title: How to find probability distribution and parameters for real data? (Python 3)
body: <p>I have a dataset from <code>sklearn</code> and I plotted the distribution of the <code>load_diabetes.target</code> data (i.e. the values of the regression that the <code>load_diabetes.data</code> are used to predict). </p>
  
  <p><em>I used this because it has the fewest number of variables/attributes of the regression <code>sklearn.datasets</code>.</em></p>
  
  <p>Using Python 3, <strong>How can I get the distribution-type and parameters of the distribution this most closely resembles?</strong> </p>
  
  <p>All I know the <code>target</code> values are all positive and skewed (positve skew/right skew). . . Is there a way in Python to provide a few distributions and then get the best fit for the <code>target</code> data/vector? OR, to actually suggest a fit based on the data that's given? That would be realllllly useful for people who have theoretical statistical knowledge but little experience with applying it to "real data". </p>
  
  <p><strong>Bonus</strong>
  Would it make sense to use this type of approach to figure out what your posterior distribution would be with "real data" ? If no, why not?</p>
  
  <pre><code>from sklearn.datasets import load_diabetes
  import matplotlib.pyplot as plt
  import seaborn as sns; sns.set()
  import pandas as pd
  
  #Get Data
  data = load_diabetes()
  X, y_ = data.data, data.target
  
  #Organize Data
  SR_y = pd.Series(y_, name="y_ (Target Vector Distribution)")
  
  #Plot Data
  fig, ax = plt.subplots()
  sns.distplot(SR_y, bins=25, color="g", ax=ax)
  plt.show()
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/ol9gk.png" rel="noreferrer"><img src="https://i.stack.imgur.com/ol9gk.png" alt="enter image description here"></a></p>