Here is an example of how to use a Series constructor in Pandas. A one-dimensional array capable of holding any data type (integers, strings, floating-point numbers, Python objects, etc.) is called a Series object in pandas.
Sample DataFrame
Single dimension data
Below is the single dimension data of Index and Value.
| Index | Value |
| 1 | 10 |
| 2 | 40 |
| 3 | 01 |
| 4 | 99 |
Having single value for an index is called Single dimensional data. On the other hand, when one index has multiple values, it is called multi-dimensional array.
Below is the example for Multi-dimensional array.
a = (1, (10,20))
mySeries = pd.Series(data, index=index)
Here, pd is a Pandas object. The data and index are two arguments. The data refers to a Python dictionary of "ndarray" and index is index of data.
Generating DataFrame from single dimension data
The below example shows, how to construct single dimension data (Values and Index).
>>>mySeries = pd.Series([10,20,30], index=[1,2, 'a'])
Special Notes: In the above index list the 'a' represents alpha type.
>>>mySeries = pd.Series([10,20,30], index=[1,2, 'a'])
Special Notes: In the above index list the 'a' represents alpha type.
Once mySeries object created, you can verify Values and Index. Do follow the steps in the screen.
