How to Replace Text in a String Column of a Pandas Dataframe
In Pandas, you may encounter situations where you need to modify the content of a text column, such as replacing a certain character or string. This can be achieved using the powerful replace method.
You mentioned having a column containing values enclosed in parentheses, with a comma separating two numbers. Your goal is to replace the comma with a dash. However, your current approach using org_info_exc['range'].replace(',', '-', inplace=True) is not working.
The issue lies in the syntax of your code. The replace method requires you to specify the exact string or regular expression to be replaced. In your case, the comma is not an exact match for the entire value.
To correctly replace the comma, you should use the following method:
<code class="python">df['range'] = df['range'].str.replace(',','-')</code>
Here, we are using the vectorized str method, which allows us to apply a string transformation to every element in the column. The replace function takes two parameters: the original string to be replaced and the new string to replace it with.
This code uses the regular expression ',' to match the comma character, regardless of its position within the string.
EDIT:
Analyzing your original attempt:
<code class="python">df['range'].replace(',','-',inplace=True)</code>
The description for this approach in the Pandas documentation states, "str: string exactly matching to_replace will be replaced with value." Since the strings in your column do not match the comma character exactly, the replacement does not occur.
Conversely, if we provide an exact match for the comma character, as shown below, the replacement will happen:
<code class="python">df = pd.DataFrame({'range':['(2,30)',',']}) df['range'].replace(',','-', inplace=True) df['range'] 0 (2,30) 1 - Name: range, dtype: object</code>
In this modified example, the second row contains an exact match for the comma, and the replacement occurs.
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