- Passing in a list of values with or without the index
```
import pandas as pd 
list1 = ["a","b","c"]
s1 = pd.Series(list1)
s2 = pd.Series(["a", "b", "c"], index = [1, 2, 3])
```
- From a dictionary. If an index isn't passed, the dictionary keys are used to create an index
```
import pandas as pd
d1 = {"a" : 1, "b" : 2, "c" : 3}
s1 = pd.Series(d1)
```
- From a scalar value. The value is repeated to match the length of the index, and the index must be provided. 
```
import pandas as pd
s = pd.Series(1, index = ["x", "y", "z"])
```

Creating a Series

In Pandas, a Series is a data structure which is a one-dimensional labeled array. The labels of a Series are known as the index. A Series can hold any data type.

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Pandas includes two main data structures: 
- Series
- DataFrame

Pandas Data Structures

https://pandas.pydata.org/docs/index.html

Pandas documentation

Pandas Series

A DataFrame is a 2-dimensional data structure, in which the data is organized in rows and columns of any type. Each column has a label, and the index of a DataFrame are the row labels. To create a DataFrame, the data can be passed in several ways: as a Series, a record or structured ndarray, a 2-D ndarray, or as a dictionary of Series, lists, or dictionaries. 

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