Зміст курсу
Time Series Analysis
Time Series Analysis
Challenge 1
Swipe to show code editor
Time for new challenges! Here is the first challenge, the idea of which is to process the pr_HH Spot Price.csv
dataset to turn it from non-stationary to stationary:
- Read the dataset.
- Test for data stationarity (use
adfuller
) and display results. - Visualize the initial values of the
"Price"
column. - Transform data (the
"Price"
column of thedf
DataFrame) from non-stationary to stationary using the difference method (using the.diff()
method withperiods = 1
parameter). Drop NA values. Assign the result to thenew_diff
variable. - Visualize the modified data (
new_diff
). - Rerun the ADF test for updated data (
new_diff
).
Дякуємо за ваш відгук!
Challenge 1
Swipe to show code editor
Time for new challenges! Here is the first challenge, the idea of which is to process the pr_HH Spot Price.csv
dataset to turn it from non-stationary to stationary:
- Read the dataset.
- Test for data stationarity (use
adfuller
) and display results. - Visualize the initial values of the
"Price"
column. - Transform data (the
"Price"
column of thedf
DataFrame) from non-stationary to stationary using the difference method (using the.diff()
method withperiods = 1
parameter). Drop NA values. Assign the result to thenew_diff
variable. - Visualize the modified data (
new_diff
). - Rerun the ADF test for updated data (
new_diff
).
Дякуємо за ваш відгук!
Challenge 1
Swipe to show code editor
Time for new challenges! Here is the first challenge, the idea of which is to process the pr_HH Spot Price.csv
dataset to turn it from non-stationary to stationary:
- Read the dataset.
- Test for data stationarity (use
adfuller
) and display results. - Visualize the initial values of the
"Price"
column. - Transform data (the
"Price"
column of thedf
DataFrame) from non-stationary to stationary using the difference method (using the.diff()
method withperiods = 1
parameter). Drop NA values. Assign the result to thenew_diff
variable. - Visualize the modified data (
new_diff
). - Rerun the ADF test for updated data (
new_diff
).
Дякуємо за ваш відгук!
Swipe to show code editor
Time for new challenges! Here is the first challenge, the idea of which is to process the pr_HH Spot Price.csv
dataset to turn it from non-stationary to stationary:
- Read the dataset.
- Test for data stationarity (use
adfuller
) and display results. - Visualize the initial values of the
"Price"
column. - Transform data (the
"Price"
column of thedf
DataFrame) from non-stationary to stationary using the difference method (using the.diff()
method withperiods = 1
parameter). Drop NA values. Assign the result to thenew_diff
variable. - Visualize the modified data (
new_diff
). - Rerun the ADF test for updated data (
new_diff
).