You can use the following syntax to get a cell value from a pandas DataFrame:
#iloc method df.iloc[0]['column_name'] #at method df.at[0,'column_name'] #values method df['column_name'].values[0]
Note that all three methods will return the same value.
The following examples show how to use each of these methods with the following pandas DataFrame:
import pandas as pd #create DataFrame df = pd.DataFrame({'points': [25, 12, 15, 14, 19, 23, 25, 29], 'assists': [5, 7, 7, 9, 12, 9, 9, 4], 'rebounds': [11, 8, 10, 6, 6, 5, 9, 12]}) #view DataFrame df points assists rebounds 0 25 5 11 1 12 7 8 2 15 7 10 3 14 9 6 4 19 12 6 5 23 9 5 6 25 9 9 7 29 4 12
Method 1: Get Cell Value Using iloc Function
The following code shows how to use the .iloc function to get various cell values in the pandas DataFrame:
#get value in first row in 'points' column df.iloc[0]['points'] 25 #get value in second row in 'assists' column df.iloc[1]['assists'] 7
Method 2: Get Cell Value Using at Function
The following code shows how to use the .at function to get various cell values in the pandas DataFrame:
#get value in first row in 'points' column df.at[0, 'points'] 25 #get value in second row in 'assists' column df.at[1, 'assists'] 7
Method 3: Get Cell Value Using values Function
The following code shows how to use the .values function to get various cell values in the pandas DataFrame:
#get value in first row in 'points' column df['points'].values[0] 25 #get value in second row in 'assists' column df['assists'].values[1] 7
Notice that all three methods return the same values.
Additional Resources
How to Convert Pandas Series to NumPy Array
How to Get First Row of Pandas DataFrame
How to Get First Column of Pandas DataFrame