Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Leer Reading and Visualizing Data | Time Series Processing
Time Series Analysis

Veeg om het menu te tonen

book
Reading and Visualizing Data

The first thing to start with is reading the data. When working with time series, the rules of the game do not change - you can still use pandas to get data from csv files.

In the files, let's say you have a Date column that contains dates in str type. For further time series analysis, you must turn the str type into a datetime. This is implemented using the pandas function to_datetime()

Let's take the dataset air_quality_no2_long.csv as an example:

python

Next, we convert the data type in the Date column from str to datetime:

python

You can also do this immediately when reading the dataset:

python

Now we can plot our dataset:

python
Taak

Swipe to start coding

Read and visualize the AirPassengers.csv dataset.

  1. Import matplotlib.pyplot as plt.
  2. Read the csv file and save it within the data variable.
  3. Convert "Month" into datetime type.
  4. Initialize a line plot with the "Month" column of data on the x-axis and "#Passengers" on the y-axis.
  5. Set labels on an axis and display the plot:
  • "Month" on the x-axis;
  • "Passengers" on the y-axis.

Oplossing

Switch to desktopSchakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande opties
Was alles duidelijk?

Hoe kunnen we het verbeteren?

Bedankt voor je feedback!

Sectie 2. Hoofdstuk 1
Onze excuses dat er iets mis is gegaan. Wat is er gebeurd?

Vraag AI

expand
ChatGPT

Vraag wat u wilt of probeer een van de voorgestelde vragen om onze chat te starten.

book
Reading and Visualizing Data

The first thing to start with is reading the data. When working with time series, the rules of the game do not change - you can still use pandas to get data from csv files.

In the files, let's say you have a Date column that contains dates in str type. For further time series analysis, you must turn the str type into a datetime. This is implemented using the pandas function to_datetime()

Let's take the dataset air_quality_no2_long.csv as an example:

python

Next, we convert the data type in the Date column from str to datetime:

python

You can also do this immediately when reading the dataset:

python

Now we can plot our dataset:

python
Taak

Swipe to start coding

Read and visualize the AirPassengers.csv dataset.

  1. Import matplotlib.pyplot as plt.
  2. Read the csv file and save it within the data variable.
  3. Convert "Month" into datetime type.
  4. Initialize a line plot with the "Month" column of data on the x-axis and "#Passengers" on the y-axis.
  5. Set labels on an axis and display the plot:
  • "Month" on the x-axis;
  • "Passengers" on the y-axis.

Oplossing

Switch to desktopSchakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande opties
Was alles duidelijk?

Hoe kunnen we het verbeteren?

Bedankt voor je feedback!

Sectie 2. Hoofdstuk 1
Switch to desktopSchakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande opties
Onze excuses dat er iets mis is gegaan. Wat is er gebeurd?
some-alt