The following examples show how to get a value from a pandas Series in three different scenarios.
Method 1: Get Value from Pandas Series Using Index
The following code shows how to get the value in the third position of a pandas Series using the index value:
import pandas as pd #define Series my_series = pd.Series(['A', 'B', 'C', 'D', 'E']) #get third value in Series print(my_series[2]) C
By specifying the index value 2, we’re able to extract the value in the third position of the pandas Series.
Method 2: Get Value from Pandas Series Using String
The following code shows how to get the value that corresponds to a specific string in a pandas Series:
import pandas as pd #define Series my_series = pd.Series({'First':'A', 'Second':'B', 'Third':'C'}) #get value that corresponds to 'Second' print(my_series['Second']) B
Using this syntax, we’re able to get the value that corresponds to ‘Second’ in the pandas Series.
Method 3: Get Value from Pandas Series in DataFrame
The following code shows how to get the value in a pandas Series that is a column in a pandas DataFrame
import pandas as pd
#create DataFrame
df = pd.DataFrame({'team': ['Mavs', 'Spurs', 'Rockets', 'Heat', 'Nets'],
'points': [100, 114, 121, 108, 101]})
#view DataFrame
print(df)
team points
0 Mavs 100
1 Spurs 114
2 Rockets 121
3 Heat 108
4 Nets 101
#get 'Spurs' value from team column
df.loc[df.team=='Spurs','team'].values[0]
'Spurs'
By using the loc and values functions, we’re able to get the value ‘Spurs’ from the DataFrame.
Related: Pandas loc vs. iloc: What’s the Difference?
Additional Resources
The following tutorials explain how to perform other common operations in pandas:
How to Convert Pandas Series to NumPy Array
How to Get First Row of Pandas DataFrame
How to Get First Column of Pandas DataFrame