Indexes and Values
Series in pandas differ from numpy arrays in that they have indexes. These can be integers, floating-point numbers, strings, time series.
To get the series' indexes, use the .index attribute of a series object. To get values, use the values attribute. By default, indexes are integers starting from 0, but if you want to change them, you simply may reassign new list of indexes to the .index attribute. For instance,
12345678910111213# Importing library import pandas as pd # Creating pandas series ser = pd.Series([1000, 2500, 1700]) # Getting series' indexes and values print(ser.index) print(ser.values) print(ser) # Changing series' indexes ser.index = ['first', 'second', 'third'] print(ser)
As you can see, initial indexes were 0, 1, 2. After changing, they became 'first', 'second', 'third'.
Tack för dina kommentarer!
Fråga AI
Fråga AI
Fråga vad du vill eller prova någon av de föreslagna frågorna för att starta vårt samtal
Ställ mig frågor om detta ämne
Sammanfatta detta kapitel
Visa verkliga exempel
Awesome!
Completion rate improved to 3.33Indexes and Values
Svep för att visa menyn
Series in pandas differ from numpy arrays in that they have indexes. These can be integers, floating-point numbers, strings, time series.
To get the series' indexes, use the .index attribute of a series object. To get values, use the values attribute. By default, indexes are integers starting from 0, but if you want to change them, you simply may reassign new list of indexes to the .index attribute. For instance,
12345678910111213# Importing library import pandas as pd # Creating pandas series ser = pd.Series([1000, 2500, 1700]) # Getting series' indexes and values print(ser.index) print(ser.values) print(ser) # Changing series' indexes ser.index = ['first', 'second', 'third'] print(ser)
As you can see, initial indexes were 0, 1, 2. After changing, they became 'first', 'second', 'third'.
Tack för dina kommentarer!
