9: Dictionaries
- Page ID
- 122394
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)- 9.1: Dictionaries
- This page discusses dictionaries as a versatile data structure that pairs keys with values, contrasting them with lists that rely on integer indices. It explains creating dictionaries using the `dict` function or curly braces, emphasizes the unpredictable order of key-value pairs, and highlights efficient value access through keys. The `len` function is used to count pairs, while the `in` operator checks key presence effectively due to hashing.
- 9.2: Dictionary as a Set of Counters
- This page discusses methods for counting letter frequencies in a string, emphasizing three approaches: 26 variables, a list, or a dictionary. The dictionary method is favored for its efficiency and straightforwardness, as it only allocates space for existing letters. An example provided illustrates how to create a histogram of letter frequencies using both a standard loop and a concise version that utilizes the dictionary's `get` method, streamlining the counting process.
- 9.3: Dictionaries and Files
- This page describes a Python program that counts word occurrences in a simplified version of "Romeo and Juliet." It processes the text line by line, splits each line into words, and uses a dictionary to count occurrences. The program utilizes nested loops for processing. The output is an unsorted dictionary of word counts, suggesting further coding is necessary to organize these results for better analysis.
- 9.4: Looping and Dictionaries
- This page explains iterating over a dictionary in Python with a for loop to access keys and values. It includes examples for printing all entries, filtering by value (greater than ten), and sorting keys alphabetically. The content highlights the unordered nature of dictionary keys, how to access specific entries based on conditions, and the output of sorted key-value pairs.
- 9.5: Advanced Text Parsing
- This page discusses processing a text file (romeo.txt) to count word occurrences, focusing on handling punctuation and capitalization using Python's string methods like `translate` and `lower`. It outlines the steps for reading the file, cleaning the text, and utilizing a dictionary for tallying word counts. It highlights the efficacy of built-in Python tools for data analysis and hints at future content on tuples for enhanced processing.
- 9.6: Debugging
- This page discusses effective strategies for debugging large datasets, including scaling down the dataset, printing summaries, implementing self-checks, performing consistency checks, and improving output formatting. These methods streamline the debugging process and help identify errors efficiently, ultimately saving time.
- 9.E: Dictionaries (Exercises)
- This page details programming exercises centered on processing email logs. It includes categorizing messages by days from commit timestamps, building a histogram of messages by email address, identifying the email address with the maximum count, and counting messages by domain names with sample outputs for clarity.
- 9.G: Dictionaries (Glossary)
- This page provides definitions of key terms related to data structures and algorithms, with an emphasis on dictionaries in Python. It covers concepts such as dictionaries, hashtables, hash functions, and their parts like keys and values. Additionally, it discusses lookup operations and nested loops, explaining their roles in computational processes. The text serves as a concise glossary for important programming and data management terminology.