The data set loaded uses a 30-year mean between 1951 and 1980 to calculate a base temperature for that period, and then uses 5-year mean temperatures to calculate the difference between the 5-year mean and the 30-year mean for each year. The scatter plot shows the annual temperature differences. We have used Linear Regression Algorithm.
Functions Used For Analysis
- head() - It shows the first N rows in the data (by default, N=5).
- shape - It shows the total no. of rows and no. of columns of the dataframe
- index - This attribute provides the index of the dataframe
- columns - It shows the name of each column
- dtypes - It shows the data-type of each column
- unique() - In a column, it shows all the unique values. It can be applied on a single column only, not on the whole dataframe.
- nunique() - It shows the total no. of unique values in each column. It can be applied on a single column as well as on the whole dataframe.
- count - It shows the total no. of non-null values in each column. It can be applied on a single column as well as on the whole dataframe.
- value_counts - In a column, it shows all the unique values with their count. It can be applied on a single column only.
- info() - Provides basic information about the dataframe.
- isna() - function is used to detect missing values. It return a boolean same-sized object indicating if the values are NA