# Convert 1/0 Integer Dummy to True/False Boolean in Columns of pandas DataFrame in Python (4 Examples)

In this article, I’ll demonstrate how to **convert an integer column to the boolean data type in a pandas DataFrame** in the Python programming language.

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Let’s get started.

## Exemplifying Data & Software Libraries

We first have to load the pandas library:

import pandas as pd # Load pandas library |

import pandas as pd # Load pandas library

Furthermore, consider the example data below:

data = pd.DataFrame({'x1':[1, 0, 1, 0, 1, 0], # Create pandas DataFrame 'x2':[1, 1, 1, 0, 0, 0], 'x3':[0, 0, 0, 1, 1, 1]}) print(data) # Print pandas DataFrame |

data = pd.DataFrame({'x1':[1, 0, 1, 0, 1, 0], # Create pandas DataFrame 'x2':[1, 1, 1, 0, 0, 0], 'x3':[0, 0, 0, 1, 1, 1]}) print(data) # Print pandas DataFrame

Table 1 shows that our example pandas DataFrame consists of six rows and three columns. Note that all our columns contain integer dummy variables (i.e. the values 1 or 0).

Let’s have a look at the data types of the columns in our pandas DataFrame:

print(data.dtypes) # Check data types of columns # x1 int64 # x2 int64 # x3 int64 # dtype: object |

print(data.dtypes) # Check data types of columns # x1 int64 # x2 int64 # x3 int64 # dtype: object

At this point, all columns in our data set have the integer data type. Please note that we could apply the same syntax to variables with the float class.

Anyway, let’s jump into the examples!

## Example 1: Convert Single pandas DataFrame Column from Integer to Boolean

This section shows how to change the data type of one single column from a 1/0 integer dummy to a True/False boolean indicator.

For this task, we can apply the astype function as you can see in the following Python code:

data_new1 = data.copy() # Create copy of DataFrame data_new1['x1'] = data_new1['x1'].astype(bool) # Transform integer to boolean print(data_new1) # Print updated pandas DataFrame |

data_new1 = data.copy() # Create copy of DataFrame data_new1['x1'] = data_new1['x1'].astype(bool) # Transform integer to boolean print(data_new1) # Print updated pandas DataFrame

By executing the previous Python code, we have created Table 2, i.e. a new pandas DataFrame where the first column has been transformed to the boolean class.

We can confirm this by having another look at the data types of our columns:

print(data_new1.dtypes) # Check data types of columns # x1 bool # x2 int64 # x3 int64 # dtype: object |

print(data_new1.dtypes) # Check data types of columns # x1 bool # x2 int64 # x3 int64 # dtype: object

As you can see, the dtype of the variable x1 has been switched from integer to boolean.

## Example 2: Convert Multiple pandas DataFrame Columns from Integer to Boolean

In Example 2, I’ll illustrate how to transform multiple dummy columns from integer to boolean.

To accomplish this, we can use the astype function once again:

data_new2 = data.copy() # Create copy of DataFrame data_new2 = data_new2.astype({'x2': bool, 'x3': bool}) # Transform multiple integers to boolean print(data_new2) # Print updated pandas DataFrame |

data_new2 = data.copy() # Create copy of DataFrame data_new2 = data_new2.astype({'x2': bool, 'x3': bool}) # Transform multiple integers to boolean print(data_new2) # Print updated pandas DataFrame

The output of the previous syntax is shown in Table 3: Another pandas DataFrame where the data types of the columns x2 and x3 have been modified.

Let’s check the column classes of our data set once again:

print(data_new2.dtypes) # Check data types of columns # x1 int64 # x2 bool # x3 bool # dtype: object |

print(data_new2.dtypes) # Check data types of columns # x1 int64 # x2 bool # x3 bool # dtype: object

The column x1 still has the integer class, but the variables x2 and x3 have been changed to the boolean data type.

## Example 3: Convert All pandas DataFrame Columns from Integer to Boolean

It is also possible to use the astype function to convert all pandas DataFrame columns from integer to boolean using the Python programming language.

In this example, I’ll demonstrate how to do that:

data_new3 = data.copy() # Create copy of DataFrame data_new3 = data_new3.astype(bool) # Transform all columns to boolean print(data_new3) # Print updated pandas DataFrame |

data_new3 = data.copy() # Create copy of DataFrame data_new3 = data_new3.astype(bool) # Transform all columns to boolean print(data_new3) # Print updated pandas DataFrame

After running the previous syntax the pandas DataFrame shown in Table 4 has been created. As you can see, the values in all columns have been adjusted.

Let’s test the column classes:

print(data_new3.dtypes) # Check data types of columns # x1 bool # x2 bool # x3 bool # dtype: object |

print(data_new3.dtypes) # Check data types of columns # x1 bool # x2 bool # x3 bool # dtype: object

The previous output confirms our result: All columns have been transformed to the boolean class.

## Example 4: Convert pandas DataFrame Column from Integer to Boolean Using apply() Function

In the previous examples, we have used the astype function to modify the data types of our pandas DataFrame columns.

The Python syntax below demonstrates how to use the apply function instead:

data_new4 = data.copy() # Create copy of DataFrame data_new4['x1'] = data_new4['x1'].apply(bool) # Transform integer to boolean print(data_new4) # Print updated pandas DataFrame |

data_new4 = data.copy() # Create copy of DataFrame data_new4['x1'] = data_new4['x1'].apply(bool) # Transform integer to boolean print(data_new4) # Print updated pandas DataFrame

After executing the previous Python code the pandas DataFrame shown in Table 5 has been created. Similar to Example 1, we have changed only the first column.

Let’ check the column data types one last time:

print(data_new4.dtypes) # Check data types of columns # x1 bool # x2 int64 # x3 int64 # dtype: object |

print(data_new4.dtypes) # Check data types of columns # x1 bool # x2 int64 # x3 int64 # dtype: object

The first column x1 has been switched from 1/0 integer to True/False boolean.

## Video & Further Resources

Would you like to learn more about the conversion of a 1/0 dummy integer column to the boolean True/False data type in a pandas DataFrame? Then you may watch the following video on my YouTube channel. I demonstrate the Python programming code of this article in the video:

*The YouTube video will be added soon.*

In addition, you may want to read the other tutorials which I have published on this website. I have released numerous articles already:

- Handling DataFrames Using the pandas Library in Python
- Convert String to Boolean in pandas DataFrame Column in Python
- Convert Float to Integer in pandas DataFrame Column
- Convert Integer to Float in pandas DataFrame in Python
- Check if Column Exists in pandas DataFrame in Python
- Add Column to pandas DataFrame in Python
- Count Unique Values by Group in Column of pandas DataFrame in Python
- Convert pandas DataFrame Index to List & NumPy Array in Python
- Convert pandas DataFrame Column to datetime in Python in R
- Introduction to Python

In summary: At this point you should know how to **convert a 1/0 dummy integer column to the boolean True/False data type in a pandas DataFrame** in Python programming. Let me know in the comments, in case you have additional questions.