What is a Series?
A Pandas Series is like a column in a table.
It is a one-dimensional array holding data of any type.
Example
import pandas as pd
a = [1, 7, 2]
myvar = pd.Series(a)
print(myvar)
Labels
If nothing else is specified, the values are labeled with their index number. First value has index 0, second value has index 1 etc.
This label can be used to access a specified value.
Example
print(myvar[0])
Create Labels
With the index argument, you can name your own labels.
Example
import pandas as pd
a = [1, 7, 2]
myvar = pd.Series(a, index = ["x", "y", "z"])
print(myvar)
When you have created labels, you can access an item by referring to the label.
Example
print(myvar["y"])
Key/Value Objects as Series
You can also use a key/value object, like a dictionary, when creating a Series.
Example
import pandas as pd
calories = {"day1": 420, "day2": 380, "day3":
390}
myvar = pd.Series(calories)
print(myvar)
Note: The keys of the dictionary become the labels.
To select only some of the items in the dictionary, use the index argument and specify only the items you want to include in the Series.
Example
import pandas as pd
calories = {"day1": 420, "day2": 380, "day3":
390}
myvar = pd.Series(calories,
index = ["day1", "day2"])
print(myvar)
DataFrames
Data sets in Pandas are usually multi-dimensional tables, called DataFrames.
Series is like a column, a DataFrame is the whole table.
Example
import pandas as pd
data = {
"calories": [420, 380, 390],
"duration":
[50, 40, 45]
}
myvar = pd.DataFrame(data)
print(myvar)
You will learn about DataFrames in the next chapter.
