I want to filter a dataframe by only keeping the rows that conform with a regex pattern in a given column. The example in the documentation only filters by looking for that regex in every column in the dataframe (documentation to filter)
So how can i change the following example
df.filter(regex='^[\d]*', axis=0)
to something like this: (Which only looks for the regex in the specified column)
df.filter(column='column_name', regex='^[\d]*', axis=0)
Use the vectorized string method contains() or match() - see Testing for Strings that Match or Contain a Pattern:
df[df.column_name.str.contains('^\d+')]
or
df[df.column_name.str.match('\d+')] # Matches only start of the string
Note that I removed superfluous brackets ([]), and replaced * with +, because the \d* will always match as it matches a zero occurrences, too (so called a zero-length match.)
Filter the DataFrame using a Boolean mask made from the given column and regex pattern as follows:
df[df.column_name.str.contains('^[\d]*', regex=True)]
