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ONE MORE?

To extract the number before specific strings in pandas, you can use regular expressions in combination with the str.extract function. First, you need to define a regular expression pattern that matches the number before the specific string you are looking for. Then, you can use the str.extract function to extract the matched number from the target column in your pandas DataFrame. This approach allows you to extract the desired number before the specific string efficiently and accurately.

How to find and extract numbers before a certain text in a pandas column?

You can use regular expressions to find and extract numbers before a certain text in a pandas column. Here's an example code snippet:

import pandas as pd import re

Create a sample DataFrame

data = {'text': ['The price is $10', 'The quantity is 20 items', 'The temperature is 25 degrees']} df = pd.DataFrame(data)

Define a function to extract numbers before a certain text

def extract_numbers_before_text(text, search_text): pattern = rf'(\d+)\s{search_text}' match = re.search(pattern, text) if match: return int(match.group(1)) return None

Apply the function to the 'text' column and create a new column with the extracted numbers

search_text = 'degrees' df['extracted_number'] = df['text'].apply(lambda x: extract_numbers_before_text(x, search_text))

print(df)

In this code snippet, we first create a sample DataFrame with a column containing text. We then define a function extract_numbers_before_text that takes a text and a search text as input, uses a regular expression to find numbers before the search text, and returns the extracted number.

We apply this function to the 'text' column using the apply method and create a new column 'extracted_number' in the DataFrame with the extracted numbers. Finally, we print the modified DataFrame.

You can adjust the search_text variable to change the text you want to search for in the 'text' column.

How to extract numerical values before a specific keyword in pandas?

To extract numerical values before a specific keyword in pandas, you can use the str.extract method along with regular expressions. Here's an example demonstrating how to extract numerical values before the keyword "apple" in a pandas DataFrame column:

import pandas as pd

Sample DataFrame

data = {'text': ['123 apple is a fruit', '456 apple is delicious', '789 banana is yellow']} df = pd.DataFrame(data)

Extract numerical values before the keyword "apple"

df['numerical_value'] = df['text'].str.extract(r'(\d+)\s+apple')

Display the DataFrame with extracted numerical values

print(df)

In this code snippet, we first create a DataFrame with a column containing text data. We then use the str.extract method with a regular expression \d+\s+apple to extract numerical values before the keyword "apple" in the text column. The extracted numerical values are stored in a new column called 'numerical_value'. Finally, we display the DataFrame with the extracted numerical values.

You can adjust the regular expression pattern to suit your specific requirements and keyword.

How to pinpoint and extract the numeric value before a specific string in pandas Series?

You can use regular expressions to accomplish this task. Here's an example code snippet that demonstrates how to pinpoint and extract the numeric value before a specific string in a pandas Series:

import pandas as pd import re

Create a sample pandas Series

data = {'text': ['The value is 123 before the string', 'Another value is 456 before the string']} df = pd.DataFrame(data)

Define a function to extract the numeric value before a specific string

def extract_numeric_value(text): pattern = r'(\d+)\s+before the string' match = re.search(pattern, text) if match: return int(match.group(1)) else: return None

Apply the function to the 'text' column in the DataFrame

df['numeric_value'] = df['text'].apply(extract_numeric_value)

Display the resulting DataFrame

print(df)

In this code snippet:

1. We create a sample pandas Series containing strings with numeric values before the specific string 'before the string'.
2. We define a function extract_numeric_value that uses a regular expression pattern to match and extract the numeric value before the specific string.
3. We apply the extract_numeric_value function to the 'text' column in the DataFrame using the apply method.
4. The resulting DataFrame will contain a new column 'numeric_value' that stores the extracted numeric values.

You can modify the regular expression pattern in the extract_numeric_value function to match different numeric value formats based on your specific requirements.