How to use Pandas Series Method top ideas
I am sharing the ideas on how to use a series constructor on a dataset using Python pandas.
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A series is an object of Pandas that represents a one-dimensional labeled array capable of holding any data type (integers, strings, floating-point numbers, Python objects, etc.).
Example of Dataframe data
Dataframe data
Example of Single Dimension Data
A single dimension data you can derive as (index, value):
| Index | Value |
| 1 | 10 |
| 2 | 40 |
| 3 | 01 |
| 4 | 99 |
So, in the above "Dataframe" when you pull out the data of a single column with its index, you can say it as one-dimensional data.
When one index has multiple values in brackets, you can say it as a multi-dimensional array. The example is (1, (10,20))
mySeries = pd.Series(data, index=index)
Here, pd is a Pandas object, and data refers to a Python dictionary of "ndarray" or even a scalar value.
How to get Values and Index using Series Method in Python Pandas
In the first example, I show how to construct single dimension data and how to get index and values from the series data.
>>>mySeries = pd.Series([10,20,30], index=[1,2, 'a'])
In the above example, in the index, I have given 'a'. So for alpha index types, you need to give in quotes.
>>>mySeries = pd.Series([10,20,30], index=[1,2, 'a'])
In the above example, in the index, I have given 'a'. So for alpha index types, you need to give in quotes.
The result from the above code is you got both values and index.
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