Python Pandas Series 
A Series is a one-dimensional labeled array. It can hold any type of data like Integer, Float, String, Python objects, etc. The label is called the index.
Pandas.Series
A Pandas Series can be created using the following constructors-
pandas.Series ( data, index, dtype, copy)
| Parameter | Description |
|---|---|
| data | data takes various forms like ndarray, list, constants |
| index | Index values must be unique. By default np.arrange(n) |
| dtype | it is a data type |
| copy | Copy data. Default false |
How to create a Pandas Series
- Array
- Dictionary
- constant
Create a Series from an array
#imports the pandas library and aliasing as pd
import pandas as pd
import numpy as np
data = np.array([‘a’,’b’,’c’,’d’,’e’])
sr=pd.Series(data)
print (sr)
| 0 | a |
| 1 | b |
| 2 | c |
| 3 | d |
| 4 | e |
#imports the pandas library and aliasing as pd
import pandas as pd
import numpy as np
data = np.array([‘a’,’b’,’c’,’d’,’e’])
sr=pd.Series(data, index=[101,102,103,104,105])
print (sr)
| 101 | a |
| 102 | b |
| 103 | c |
| 104 | d |
| 105 | e |
Create a Series from a dictionary
#imports the pandas library and aliasing as pd
import pandas as pd
data = {‘a’ : 0, ‘b’ : 1, ‘c’ : 2, ‘d’ : 3}
sr=pd.Series(data)
print (sr)
| a | 0 |
| b | 1 |
| c | 2 |
| d | 3 |
Create a Series from constant
#imports the pandas library and aliasing as pd
import pandas as pd
sr=pd.Series(4, index=[0,1,2,3])
print (sr)
| 0 | 4 |
| 1 | 4 |
| 2 | 4 |
| 3 | 4 |
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