Str.contains in Pandas Workout: 200 exercises to make you a stronger data analyst

Q: How deeply does Pandas Workout: 200 exercises to make you a stronger data analyst cover str.contains?

Explains Boolean-mask use, regular-expression patterns, punctuation cleanup, and explicit `regex=True`, without detailing matching internals.

A pandas string-accessor method that tests each string value against a substring or regular expression and returns Boolean results.

`str.contains` searches each value in a pandas Series for a pattern and returns a Boolean Series with the same index. Treat the result as a row-by-row answer sheet: `True` marks values that match, and that Boolean Series can directly filter the original data. section 9.0 section 9.2

Table 9.1 What you need to know (view table figure)

Concept	What is it?	Example	To learn more
`s.explode`	Returns a new series with each element on its own line	`s.explode()`	http://mng.bz/RxDP
`str.contains`	Returns a series of booleans, indicating which elements of the input series contain the target string	`s.str.contains('a')`	http://mng.bz/2D2X
`str.get_dummies`	Returns a data frame containing 1s and 0s based on a categorical series	`s['country']. get_dummies (sep=';')`	http://mng.bz/1q2g
`str.index`	Returns a series of integers, each indicating where the target string was found in the corresponding element of the input series	`s.str.index('a')`	http://mng.bz/PzEP
`str.len`	Returns a series of integers indicating the length of each element	`s.str.len()`	http://mng.bz/Jg0v
`str.replace`	Returns a series based on an existing series, replacing the first argument with the second	`s.str.replace('a', 'e')`	http://mng.bz/wv6Q
`str.split`	Returns a series in which each element is a list of strings; the argument specifies the delimiter used to perform the split	`s.str.split(';')`	http://mng.bz/qrD2
`str.strip`	Returns a series of Python strings without the argument’s characters on either side	`s.str.strip('.!?')`	http://mng.bz/7D2y
`s.isin`	Returns a boolean series indicating whether a value in `s` is an element of the argument	`s.isin(['A', 'B', 'C'])`	http://mng.bz/mVW2
`i.intersection`	Returns a new index object containing elements in two existing index objects	`i.intersection(i2)`	http://mng.bz/5w21

Use this compact reference to place `str.contains` among related Series string operations: it tests whether each element contains a target string. section 9.0

Select respondents who reported Python

Survey language responses can contain several semicolon-separated values, such as `Python;JavaScript`. First remove missing `LanguageHaveWorkedWith` values, because applying `str.contains` to `NaN` causes an error. Then use the Boolean result to retain matching rows: `so_df = so_df.dropna(subset=['LanguageHaveWorkedWith'])` `so_df = so_df.loc[so_df['LanguageHaveWorkedWith'].str.contains('Python')]` This identifies respondents whose reported languages include `Python`, while leaving later analysis free to compare their experience distribution with another survey. section 8.2 section 8.2

The search pattern can be a regular expression, not merely literal text. For example, `[ae]` matches words containing either `a` or `e`. Be explicit with `regex=True` when regular-expression behavior is intended, rather than relying on a default that may change. section 9.0

Find capitalized words

A regular expression can describe the whole word, not just a substring. `^[A-Z]\w*$` matches a word that begins with an uppercase letter and continues through its end with zero or more alphanumeric characters. The anchors `^` and `$` make the test apply to the entire value, and `\w*` retains single-letter words such as `A` and `I`. `capitalized = s.str.contains('^[A-Z]\w*$', regex=True)` `words = s.loc[capitalized]` Clean punctuation first when quoted or punctuated words would otherwise hide an initial capital: `s.str.strip(string.punctuation).str.contains('^[A-Z]\w*$', regex=True)`. Apply that mask back to `s`, then use `count()` to total the selected words. section 9.2 section 9.2

Use the result as part of a broader filtering workflow:

Remove missing values in the searched column before testing it when missing entries would cause an error. section 8.2
Store or immediately use the Boolean Series as a mask with `.loc` to keep matching values or rows. section 9.0 section 9.2
Chain other string methods before searching when normalization matters, such as stripping punctuation before testing capitalization. section 9.2
Count selected values after filtering when the analytical question asks how many matches occur. section 9.2

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