If you are a beginner in data science or data analysis, you might have come across the Pandas Python library. Pandas is easy to use for data analysis. It offers the incentive to work with different kinds of data. Pandas provides a variety of tools to work with data, for instance:
Data Analysis tools for cleaning, analyzing and summarizing the data
Data structures for storing and manipulating the data
Data visualization tools for creating charts and graphs
Data Analysis Tools
Pandas provides a variety of tools for exploring, cleaning and removing duplicate data using Python.
Pandas can be used for summarizing the data, creating plots and performing statistical analysis,
Pandas can be used to summarize a given dataset by calculating descriptive statistics, such as mean, mode and standard deviation.
Pandas can be used to impute missing values.
Pandas can be used to create graphs and charts and visualize the data.
Data Visualization Tools
Pandas can be used to provide a wide variety of ways for creating graphs and charts for instance, line charts and bar charts
Line charts: Pandas can be used to create line charts, since line charts show the relationship between variables
Bar charts: Bar charts are used to show the frequency of categorical data
Scatter plots: Scatter plots can be used to the relationship between two variables.
Pie charts: Pie charts are used to show the relative proportions of different parts of a whole.
I hope you found this blog post useful. In my next article, I will be discussing the pandas Python library in more detail.