What is pandas?

• a Python package that provides fast, flexible and expressive data structures
• designed to work with relational and labeled data
• it is suited to work with:
  • tabular data with heterogenous types
  • ordered and unordered times series data
  • arbitrary matrix data
  • observational /statistical data sets
• pandas is fast, many high-performance algorithms under the hood

pandas does well:

• handling of missing
• mutable data structures (inserting and deleting data)
• automatic and explicit data alignment
• flexible groupby functionality and advanced data querying
• high interperability with NumPy and SciPy
• easy and intelligent slicing, indexing and subsetting of large data sets
• intuiting merging and joining of data
• hierarchical and multilevel datasets
• robust i/o operations to read and write multiple data formats
• time series specific functionality

pandas Data Structures

• Series - 1-D labeled homogeneously-typed array (that type may be object)
• DataFrame - General 2D labeled, size mutable tabular structure with potentially heterogenous-typed columns

pandas DataFrame