Data types are the types of data that a variable is holding. Based on the datatype the mathematical calculation, function, result, and statistical model depend. Different columns have different types of numbers even some columns are not number-based, special character-based, alphabet-based, etc. Output columns also have some requirements. Before telling about data types importance and conclusion in data analysis just quick look at all the data types
| Common data types | Details | Example |
| Integer (int) | Whole numbers, both positive and negative, without decimal points | 1,-7,40 |
| Float (float) | Numbers with decimal points | 1.12,-2.69,1.1 |
| String (str) | Text, characters, or a sequence of characters | hello, excel, I am |
| Boolean (bool) | Either True or False, typically used for logical operations and conditions | True and False |
| List | An ordered collection of items that can be of different data types. Lists are mutable, meaning their elements can be changed | [5, “mango”, 4.49] |
| Tuple | Similar to lists but immutable, meaning their elements cannot be changed after creation | (1, “sugar”, 8.21) |
| Dictionary (dict) | A collection of key-value pairs. Each key is associated with a value | {“apple”, 5, 6.80} |
| Set | An unordered collection of unique elements. Sets do not allow duplicate values | {1.12, “life”, 13} |
| None | Absence of value | null |
| Complex (complex) | Complex numbers with real and imaginary parts | 2-2j |
| Date and Time | Dates and times, allowing for date calculations and formatting | dates and times |
| Custom Objects | You can define your own data types by creating classes and objects with attributes and methods | customized |
Importance of data types
Choosing the proper data types is crucial for memory usage and processing. Different programming languages have different specializations in data types. In data analysis or data science, we have to play with the data. Output data and input data have features and in the features, we deal with different data types. Output feature data types, and input feature data type matter most for choosing proper mathematical models and statistical models. Like regression, classification, etc. Similarly, making models, data preprocessing, etc. Furthermore, the time series analysis is for the feature of date and time data type. That’s why, we have to understand the data types very well for doing anything.
Conclusion
The data types importance and conclusion in data analysis or data science are based on the data which you have. Furthermore, what you want to do. Data is everything and AI and ML are largely based on data. If we don’t have data then a model would not be created. For working or developing something through any programming language we have to see the data, features and data types. Output and result are everything, depending upon data and data types.
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