Pandas Series
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
Create a simple Pandas Series from a list:
import pandas as pd
a = [1, 7, 2]
myvar = pd.Series(a)
print(myvar)
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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.
Create Labels
With the index argument, you can name your own labels.
Example
Create your own labels:
import pandas as pd
a = [1, 7, 2]
myvar = pd.Series(a, index = ["x", "y", "z"])
print(myvar)
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When you have created labels, you can access an item by referring to the label.
Key/Value Objects as Series
You can also use a key/value object, like a dictionary, when creating a Series.
Example
Create a simple Pandas Series from a dictionary:
import pandas as pd
calories = {"day1": 420, "day2": 380, "day3": 390}
myvar = pd.Series(calories)
print(myvar)
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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
Create a Series using only data from "day1" and "day2":
import pandas as pd
calories = {"day1": 420, "day2": 380, "day3": 390}
myvar = pd.Series(calories, index = ["day1", "day2"])
print(myvar)
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DataFrames
Data sets in Pandas are usually multi-dimensional tables, called DataFrames.
Series is like a column, a DataFrame is the whole table.
Example
Create a DataFrame from two Series:
import pandas as pd
data = {
"calories": [420, 380, 390],
"duration": [50, 40, 45]
}
myvar = pd.DataFrame(data)
print(myvar)
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You will learn about DataFrames in the next chapter.