mirror of
https://github.com/BinRoot/Haskell-Data-Analysis-Cookbook.git
synced 2024-09-11 06:15:31 +03:00
| .. | ||
| Code01_whitespace | ||
| Code02_punctuation | ||
| Code03_unexpected | ||
| Code04_regex | ||
| Code05_lex | ||
| Code06_combining | ||
| Code07_dedup | ||
| Code08_freq | ||
| Code09_freq2 | ||
| Code10_manhattan | ||
| Code11_euclid | ||
| Code12_pearson | ||
| Code13_cos | ||
| LICENSE | ||
| README.md | ||
Chapter 2
Chapter 2, Integrity and Inspection, explains the importance of cleaning data through recipes about trimming whitespace, lexing, and regular expression matching.
This is the accompanying source code for Haskell Data Analysis Cookbook. Refer to the book for step-by-step explanations.
Recipes
- Code01: Trimming excess whitespace
- Code02: Ignoring punctuation and specific characters
- Code03: Coping with unexpected or missing input
- Code04: Validating records by matching regular expressions
- Code05: Lexing and parsing an e-mail address
- Code06: Deduplication of nonconflicting data items
- Code07: Deduplication of conflicting data items
- Code08: Implementing a frequency table using Data.List
- Code08: Implementing a frequency table using Data.MultiSet
- Code10: Computing the Manhattan distance
- Code11: Computing the Euclidean distance
- Code12: Comparing scaled data using the Pearson correlation coefficient
- Code13: Comparing sparse data using cosine similarity
How to use
Setting up the environment
Install the Haskell Platform.
$ sudo apt-get install haskell-platform
Alternatively, install GHC 7.6 (or above) and Cabal.
$ sudo apt-get install ghc cabal-install
Running the code
A Makefile is provided in each recipe. Compile the corresponding executable by running make.
$ make
Run the resulting code. For example,
$ ./Code01
To clean up the directory:
$ make clean