If you are a data analyst or work with a lot of data, you might have come across the Pandas library for data manipulation. In this tutorial, we will examine how we can get a value of a cell from a Pandas DataFrame.
Related Tutorial: 5 Minutes to Pandas
There are 5 ways to extract value from a cell of a Pandas DataFrame
- Extract data using
iloc
or indexing - Extract data using
iat
- Extract data using
loc
- Extract data using
at
- Extract data using
data_frame.values[]
Loading the Dataset
We will examining the above methods by loading a sample dataset. I have used the California housing dataset that you can download from this link.
import pandas as pd data = pd.read_csv('sample_data/california_housing_test.csv')
Let us see the columns of the dataset
data.head(5)
Output
We can see the first 5 rows of the dataset. The dataset has 9 columns. We will now examine the 5 different methods to extract the 2nd row value of the latitude column
Method 1: Extract Data using iloc or Indexing
We can use normal indexing the extract the value.
data.iloc[1]['latitude']
Since the indexing starts from 0, the 1st index is used to get the contents for the 2nd row. Once we extract the row, we can extract any column value that we want. In our case we wanted to get the latitude value. We get the following output.
Output
34.26 |
Method 2: Extract Data using iat
We will not look at another method to extract the latitude value from the 2nd row.
We can call the iat
method of the pandas dataframe to get the cell value. The iat
value is called using the row index and column index as an argument. In our example latitude is the 1st column index and for the 2nd row we will use the 1st Index.
data.iat[1,1]
Output
34.26
Method 3: Extract Data using loc
We can use the loc method to get the value. The loc method unlike the ioc method can be used by passing in a string as an argument if the index values are strings. In our example since all indexes are numerical values, we can do the following
data.loc[1]['latitude']
Output
34.26
Method 4: Extract Data using at
The fourth way to extract a value from the cell is using the at
method. The at
method takes in the row index as an argument and the column name as the second argument.
data.at[1,'latitude']
Output
34.26
Method 5: Extract Data using data_frame.values[]
The last method to extract the value from a specific cell is to first convert the frame into a series by using the column name we are interested in getting the value from and then converting the series into a list using the values property. We can then use normal row indexing to get the value from a specific row.
data['latitude'].values[1]
Output
34.26
👉 Recommended Tutorial: Python Find Longest String in a DataFrame Column
Summary
In this blog post, we saw 5 methods to extract the value from a pandas dataframe. Depending on the use case, we can use any of the above 5 methods to get a value from a cell.
Programming Humor
💡 Programming is 10% science, 20% ingenuity, and 70% getting the ingenuity to work with the science.
~~~
- Question: Why do Java programmers wear glasses?
- Answer: Because they cannot C# …!
Feel free to check out our blog article with more coding jokes. 😉