• X (Data): Array or sequence of arrays to be plotted on Histogram

• a) Single Array
  

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  import matplotlib.pyplot as plt l = [1,4,7,12,13,15] plt.hist(l) plt.show()

  Find the output of the above program, all the bucket or bins taken by the Python by default.
  
• b) Tow or more than two arrays

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  import matplotlib.pyplot as plt a = [1,4,7,12,13,15] b = [10,14,17,2,3,11] plt.hist([a,b]) plt.show()

  Since in the above program, we are providing two sequences here the Python will generated two histograms as below:
  

• bins: an integer or sequence, used to divide the range in the histogram

• a) Automatic bins: In the previous two examples you can see that I have not given bins parameter. Bin is dividing automatically.
• b) Giving the bins Manually 
  i) Using Scalar Value
  

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  import matplotlib.pyplot as plt a = [1,4,7,12,13,15] plt.hist(a, bins=5) plt.show()

  You can see I have given bins as 5, hence python will create 5 bins of equal size. 
  
  
  ii) Using list
  

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  import matplotlib.pyplot as plt a = [1,4,7,12,13,15] plt.hist(a, bins=[1,5,10,15]) plt.show()

  In the above program, since we are giving bins as a list, hence now bins will be 1-5,5-10 and 10-15.
  

• cumulative: To make a cumulative histogram, by default it is False

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import matplotlib.pyplot as plt
a = [1,4,7,12,13,15]
plt.hist(a, bins=[1,5,10,15], cumulative=True)
plt.show()

• histtype: This gives the style to the histogram.
  

• 'bar' [Defaut]
• 'barstacked': Used when providing two or more arrays as data
• 'step': generate a line plot that is by default unfilled  
• 'stepfilled': generate a filled line plot

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import matplotlib.pyplot as plt
a = [1,4,7,12,13,15]
b = [11,14,17,2,3,12]

plt.subplot(2,2,1)
plt.hist(a, bins=[1,5,10,15], histtype='bar')
plt.title("bar")

##barstacked is used with two or more data arrays
plt.subplot(2,2,2)
plt.hist([a,b], bins=[1,5,10,15], histtype='barstacked')
plt.title("barstacked")

plt.subplot(2,2,3)
plt.hist(a, bins=[1,5,10,15], histtype='step')
plt.title("step")

plt.subplot(2,2,4)
plt.hist(a, bins=[1,5,10,15], histtype='stepfilled')            
plt.title("stepfilled")

plt.show()

• align: Used for Histogram bars alignment{'left', 'mid', 'right'}, default is 'mid'

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import matplotlib.pyplot as plt
a = [1,4,7,12,13,15]
plt.subplot(1,3,1)
plt.hist(a, bins=[1,5,10,15], align='mid')
plt.title("MID")

plt.subplot(1,3,2)
plt.hist(a, bins=[1,5,10,15], align='right')                  
plt.title("RIGHT")

plt.subplot(1,3,3)
plt.hist(a, bins=[1,5,10,15], align='left')
plt.title("LEFT")

plt.show()

• orientation: Used for making a histogram 'horizontal' or 'vertical' [Default]

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import matplotlib.pyplot as plt
a = [1,4,7,12,13,15]
plt.subplot(1,2,1)
plt.hist(a, bins=[1,5,10,15], orientation='horizontal')           
plt.title("HORIZONTAL")

plt.subplot(1,2,2)
plt.hist(a, bins=[1,5,10,15], orientation='vertical')
plt.title("VETICAL")

plt.show()

• The Index taken by Dictionary
• Specifying Index Using List
• Indexes with Scalar Data Value

a) The index taken by Dictionary

import pandas as pd
d = {'A':1, 'B':2, 'C':3}
print(d)
s = pd.Series(d)
print(s)
print(type(s))

'''
Output:
------
{'A': 1, 'B': 2, 'C': 3}

A    1
B    2
C    3
dtype: int64

<class 'pandas.core.series.Series'>
'''

import pandas as pd
l = [1,2,3]
s = pd.Series(data= l, index = ['X','Y','Z'])
print(s)
'''
Output
------
X    1
Y    2
Z    3
dtype: int64
'''

l = [1,2,3]
s = pd.Series(l, ['X','Y','Z'])
print(s)
'''
Output
------
X    1
Y    2
Z    3
dtype: int64
'''