Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.Data Type Conversion | Time Series Data Processing
Data Preprocessing

Data Type ConversionData Type Conversion

Data type conversion in time series data processing is the process of converting time series data from one data type to another. Why do we need to use that? In time series data processing, this can be useful when you want to change your data format to make it easier to work with or when you want to perform calculations that require a different data type.
For example, you might convert a string representation of a date into a datetime object so that you can perform calculations on it.

Let's look at an example of converting date data from string format to datetime format:

You can change the format of the date entry template with the format argument.

We can consider different date patterns:

  • '15 Jul 2009' - '%d %m %Y';
  • '1-Feb-15' - '%d-%m-%Y';
  • '12/08/2019' - '%d/%m/%Y'.

Also, take into account that when we talk about processing time-series data, this means that we will work not only with dates but with all other data types (numeric, categorical, etc.).

Task

Read the 'sales.csv' dataset and convert the 'Date' column to the datetime data type.

Everything was clear?

Section 4. Chapter 1
toggle bottom row
course content

Course Content

Data Preprocessing

1. Brief Introduction

Data TypesData Processing MethodsDataset: Test and TrainingDeleting an "Extra" DataChanging the Data Type

2. Processing Quantitative Data

Data ScalingData Scaling vs Data NormalizationRemoving OutliersRemoving Missing ValuesData Augmentation: Synthetic Data

3. Processing Categorical Data

Methods for Encoding the Categorical DataOne-Hot EncodingOrdinal EncodingLabel Encoding of the Target VariableChallenge

4. Time Series Data Processing

Data Type ConversionData CleaningStationarityDenoisingTrain/Test Split & Cross ValidationChallenge

5. Feature Engineering

Technique IdeaRealizationFeature Extraction from TextFeature Extraction from ImagesFeature Extraction from Time SeriesChallenge

6. Moving on to Tasks

Challenge 1Challenge 2Challenge 3

Data Preprocessing

Data Type ConversionData Type Conversion

Data type conversion in time series data processing is the process of converting time series data from one data type to another. Why do we need to use that? In time series data processing, this can be useful when you want to change your data format to make it easier to work with or when you want to perform calculations that require a different data type.
For example, you might convert a string representation of a date into a datetime object so that you can perform calculations on it.

Let's look at an example of converting date data from string format to datetime format:

You can change the format of the date entry template with the format argument.

We can consider different date patterns:

  • '15 Jul 2009' - '%d %m %Y';
  • '1-Feb-15' - '%d-%m-%Y';
  • '12/08/2019' - '%d/%m/%Y'.

Also, take into account that when we talk about processing time-series data, this means that we will work not only with dates but with all other data types (numeric, categorical, etc.).

Task

Read the 'sales.csv' dataset and convert the 'Date' column to the datetime data type.

Everything was clear?

Section 4. Chapter 1
toggle bottom row
some-alt