The dataset "GlobalLandTemperaturesByCountry.csv" contains temperature data for various countries across the world spanning from the year 1750 to 2015. Each record in the dataset represents a country's temperature observations for a particular month, and includes features such as average, minimum and maximum temperatures, and temperature uncertainty. By analyzing this data, we can gain insights into how global temperatures have changed over time and how they vary across different regions. This information can be used to inform policy decisions related to climate change mitigation and adaptation, as well as to develop strategies for managing the impact of climate change on local economies and ecosystems.
import pandas as pd
df_temp_chart = pd.read_csv('GlobalLandTemperaturesByCountry.csv')
df_temp_chart.dropna(how='any', inplace=True)
df_temp_chart.head()
dt | AverageTemperature | AverageTemperatureUncertainty | Country | |
---|---|---|---|---|
0 | 1743-11-01 | 4.384 | 2.294 | Åland |
5 | 1744-04-01 | 1.530 | 4.680 | Åland |
6 | 1744-05-01 | 6.702 | 1.789 | Åland |
7 | 1744-06-01 | 11.609 | 1.577 | Åland |
8 | 1744-07-01 | 15.342 | 1.410 | Åland |
This dataset provides a detailed history of past temperature data for many nations, making it suitable for evaluating trends and patterns in global temperature swings over the last 250+ years.
The data can be used to identify countries or regions that are most vulnerable to climate change, such as those experiencing more frequent extreme and unusual weather patterns or dramaticly rising temperatures. It can further be used to influence climate change mitigation and adaptation policy decisions, as well as to build strategies for controlling the impact of climate change on local economies and ecosystems.