Iterating Over Strings

Counting What Appears

Suppose you need to analyze a word and determine how often each character appears. For the word brontosaurus, the letters r, o, s, and u each appear twice, while b, n, t, and a appear once. This kind of frequency count records how often each item occurs.

The counting problem has three common strategies: use separate variables, use a list, or use a dictionary. All three can represent frequencies, but they differ in how much information must be known before processing begins and how much storage is reserved.

Three Storage Strategies

Separate variables and a fixed-size list require planning. For example, using 26 variables or a 26-element list reserves room for every letter of the alphabet, whether or not every letter appears. The list approach can work when the input is restricted to English letters and characters are converted to indices with ord(), but it depends on that known range.

A dictionary takes a different approach. It creates an entry only when a character actually appears. This means the dictionary does not require you to decide in advance exactly which characters the input will contain.

The Dictionary Decision

The dictionary algorithm uses one decision for every character. If the character is not already a key in the dictionary, add it with a count of 1. If it is already present, increase its existing count by 1. The pattern is if c not in d: initialize; otherwise: increment.

text = "brontosaurus" d = {} for c in text: if c not in d: d[c] = 1 else: d[c] = d[c] + 1 print(d)

Tracing Each Character

The word brontosaurus contains 12 characters but only 8 unique letters. The dictionary changes whenever the loop reads a character for the first time, and it changes an existing value whenever a repeated character is encountered.

Why Dictionaries Adapt

The dictionary approach is useful when the possible input is not known ahead of time. A string might contain letters, digits, punctuation, or Unicode symbols. A fixed list would require you to know the full range of possible characters and their numeric codes, while a dictionary can create keys for the characters that actually arrive.

The same check-and-update pattern also extends beyond characters. The source describes the pattern as useful for frequency tables, tallies, and histograms, and notes that it can be adapted to counting words or analyzing text in multiple languages.

Common Counting Mistakes

• Incrementing a dictionary key before creating it.

  A new character does not yet have a counter in the dictionary.

  Fix: Check whether c is in d. Create d[c] with value 1 when it is new; otherwise increment the existing value.

• Treating every character as a repeated character.

  The first occurrence of a character needs initialization rather than an update.

  Fix: Use the if c not in d decision to distinguish first occurrences from later occurrences.

• Choosing a fixed list without considering the input.

  The list approach requires the possible character range and numeric codes to be known.

  Fix: Use a dictionary when the input can contain characters outside a known fixed range.

• Assuming the dictionary must contain every possible character.

  The dictionary approach creates entries only for characters that actually appear.

  Fix: Interpret the dictionary as a record of observed characters and their frequencies.

Practice the Trace

Key Takeaways

1. Character frequencies can be stored with separate variables, a list, or a dictionary.
2. Variables and fixed lists require the possible character set to be decided in advance.
3. The dictionary pattern checks whether a character is already present, then initializes or increments its count.
4. A dictionary stores only characters that actually appear, so it adapts to letters, digits, punctuation, and Unicode symbols.
5. The dictionary is a histogram: its keys are the observed items and its values are their frequencies.