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In this Python for Time Series Data Analysis course, you’ll get a depth learning of Python for time series analysis. Do you know what time series python is? If not then here we have gathered some useful information regarding it. Or you can learn more about from the Python for Time Series Data Analysis course. Time series is a series of observation which is observed at the various time intervals. It mainly depends on the frequency of the observation and it can be hourly, weekly, daily, monthly as well as annual. There can be also minute wise or second wise time series.
To learn more about the time series analysis Python, the Python for Time Series Data Analysis course is your choice. Next, let’s see some details of the course.
Some details of the course:
- Course name: Python for Time Series Data Analysis
- Mentor: Jose Portilla
- Platform: Udemy
- Rating: 4.6 (339 ratings)
- Popularity: 2,808 students enrolled
- Language: English and closed English captions
- Update date: Last updated 4/2019
- Video: 15 hours of on-demand video
- Resources: 1 article, 3 downloadable resource
- Lectures: 92 lectures
- Requirement: A certain level of Python knowledge
- Target: Python developers
Why analyze the time series?
The reason we need to analyze the time series is because it is initial step is is done before we develop the forecast of a series. Great commercial significance are observed by analyzing the time series. Sales and demand, a number of viewers to a website, etc can be recorded as time series data by the commercial companies.
If you thinking that what a time series analysis involves then let me tell you that it involves the understanding inherent nature of the series and the aspects which are related to it. By analyzing the time series one get better informed to create accurate as well as meaningful forecast. To be a master in forecasting time series data, the Python for Time Series Data Analysis course can help you.
Patterns in the time series-
In the Python for Time Series Data Analysis course, you’ll have a deep learning on how to forecast time series data. A time series have some parts which are mentioned below-
The trend is the rising or the falling of the observation in a series. Also, the seasonality is distinct repeated pattern which is observed by the user at regular intervals and this happens due to the seasonal factor. These seasonal factors can be month of the year, weekdays, and day of the months or even time of day.
Al time series essentially have the trends as well as seasonality in them. A time series does not have a distinct trend, however, have seasonality. Thus, time series can be imagined as the mixture of the trend, error terms as well as seasonality.
Looking to master the Python programming Language for time series analysis? Don’t miss out on learning the hot and new course of Python for Time Series Data Analysis at Udemy.
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