22 docs tagged with "pandas"

Aggregation combines multiple values into a single summary value. Common operations include sum, mean, count, min, max, and custom aggregations.

pandas provides several methods to apply custom functions to data:

Binning converts continuous data into discrete intervals (bins). Categorical data represents discrete categories with limited unique values. Both are essential for analysis and visualization.

Boolean filtering selects rows based on conditions. It's one of the most common operations in data

pandas has three fundamental data structures:

Understanding and managing data types is crucial for:

Working with dates and times is essential for time series analysis. pandas provides powerful datetime functionality through:

GroupBy implements the split-apply-combine pattern:

Duplicate rows are common in real-world data. _pandas_ provides simple methods to find and remove them.

Common pandas questions asked in data science and analytics interviews. Each snippet includes the problem, solution, and explanation.

_pandas_ provides two main indexers for selecting data:

pandas provides several methods to combine DataFrames:

Missing data appears as NaN (Not a Number), None, or NaT (Not a Time) in pandas. Handling it correctly is crucial for data analysis.

Outliers are data points that differ significantly from other observations. Data validation ensures your data meets expected criteria before analysis.

What is Pandas?

Pivot tables and melt are powerful reshaping tools:

_pandas_ can read from and write to many file formats. The most common pattern is pd.read_*()

Time series analysis often requires:

Reshaping transforms data between wide and long formats. Common operations:

Column selection is one of the most common operations in _pandas_. There are several ways to

Sorting organizes data by values. Ranking assigns positions based on values. Both are essential for analysis and presentation.

pandas provides string methods through the .str accessor. These methods work on Series containing strings and are essential for text data cleaning.