Let's find out how many dwellings of each type are in the dataframe. Below the task description you can find code meanings.

|DESCRIPTION|CODE|
|---|---|       
|Single-detached house|1| 
|Apartment in build. 5+ storeys|2| 
|Apartment in build. <5 storeys|3| 
|Semi-detached house|4| 
|Apartment in a detached duplex|5| 
|Row house|6| 
|Other single-attached house|7|
|Mobile home or other movable|8|

The data received from different sources can be messy, and to use it in the future, you must ensure it is convenient. In the first section, you will learn what data preprocessing is and will deal with some logical inconsistencies.

Missing or NA values, outliers, and inconsistencies are other types of problematic data. Throughout the second section of the course, you will learn how to deal with such issues.

As a data analyst, you will need to draw compact conclusions based on large amounts of data. In order to achieve that, you need to understand the data grouping idea and how to apply it to examples.

Sometimes one built-in function is not enough to draw a complete conclusion, so you need to use something more complex. This section will teach you how to apply multiple functions while grouping. Also, you will learn to visualize data using the pandas library only and will be acquainted with the main plot types. As a data analyst, you will need to draw compact conclusions based on large amounts of data. In order to achieve that, you need to understand the data grouping idea and how to apply it to examples.

As mentioned before, sometimes you may need to work with data received from multiple sources. This section will teach you how to join two dataframes using different techniques.