pandas.Series.replace¶
-
Series.
replace
(to_replace=None, value=None, inplace=False, limit=None, regex=False, method='pad', axis=None)[source]¶ Replace values given in ‘to_replace’ with ‘value’.
Parameters: to_replace : str, regex, list, dict, Series, numeric, or None
str or regex:
- str: string exactly matching to_replace will be replaced with value
- regex: regexs matching to_replace will be replaced with value
list of str, regex, or numeric:
- First, if to_replace and value are both lists, they must be the same length.
- Second, if
regex=True
then all of the strings in both lists will be interpreted as regexs otherwise they will match directly. This doesn’t matter much for value since there are only a few possible substitution regexes you can use. - str and regex rules apply as above.
dict:
- Nested dictionaries, e.g., {‘a’: {‘b’: nan}}, are read as follows: look in column ‘a’ for the value ‘b’ and replace it with nan. You can nest regular expressions as well. Note that column names (the top-level dictionary keys in a nested dictionary) cannot be regular expressions.
- Keys map to column names and values map to substitution values. You can treat this as a special case of passing two lists except that you are specifying the column to search in.
None:
- This means that the
regex
argument must be a string, compiled regular expression, or list, dict, ndarray or Series of such elements. If value is alsoNone
then this must be a nested dictionary orSeries
.
- This means that the
See the examples section for examples of each of these.
value : scalar, dict, list, str, regex, default None
Value to use to fill holes (e.g. 0), alternately a dict of values specifying which value to use for each column (columns not in the dict will not be filled). Regular expressions, strings and lists or dicts of such objects are also allowed.
inplace : boolean, default False
If True, in place. Note: this will modify any other views on this object (e.g. a column from a DataFrame). Returns the caller if this is True.
limit : int, default None
Maximum size gap to forward or backward fill
regex : bool or same types as to_replace, default False
Whether to interpret to_replace and/or value as regular expressions. If this is
True
then to_replace must be a string. Otherwise, to_replace must beNone
because this parameter will be interpreted as a regular expression or a list, dict, or array of regular expressions.method : string, optional, {‘pad’, ‘ffill’, ‘bfill’}
The method to use when for replacement, when
to_replace
is alist
.Returns: filled : NDFrame
Raises: AssertionError
- If regex is not a
bool
and to_replace is notNone
.
TypeError
- If to_replace is a
dict
and value is not alist
,dict
,ndarray
, orSeries
- If to_replace is
None
and regex is not compilable into a regular expression or is a list, dict, ndarray, or Series.
ValueError
- If to_replace and value are
list
s orndarray
s, but they are not the same length.
See also
NDFrame.reindex
,NDFrame.asfreq
,NDFrame.fillna
Notes
- Regex substitution is performed under the hood with
re.sub
. The rules for substitution forre.sub
are the same. - Regular expressions will only substitute on strings, meaning you cannot provide, for example, a regular expression matching floating point numbers and expect the columns in your frame that have a numeric dtype to be matched. However, if those floating point numbers are strings, then you can do this.
- This method has a lot of options. You are encouraged to experiment and play with this method to gain intuition about how it works.