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Advanced Data Analytics with AWS: Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows Across Diverse Data Sources (English Edition)
Univariate, Bivariate, and Multivariate Statistics Using R: Quantitative Tools for Data Analysis and Data Science
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Data Science Foundations Tools and Techniques: Core Skills for Quantitative Analysis with R and Git (Addison-Wesley Data & Analytics Series)
To return a specific substring within a pandas dataframe, you can use the str.extract() function along with regular expressions. First, you can specify the column containing the text data that you want to extract the substring from. Then, use the str.extract() function with a regular expression pattern to define the substring you want to extract. The extracted substrings can then be stored in a new column or used for further analysis. It is important to ensure that the regular expression pattern correctly matches the desired substring within the text data.
How to get the last 5 characters from a string in a pandas dataframe?
You can use the str accessor in pandas to access the last 5 characters of a string in a dataframe column. Here's an example code snippet to demonstrate:
import pandas as pd
Create a sample dataframe
data = {'text': ['abcdef', 'ghijklm', 'nopqrst']} df = pd.DataFrame(data)
Extract the last 5 characters from the 'text' column
df['last_5_chars'] = df['text'].str[-5:]
print(df)
This code will create a new column in the dataframe called last_5_chars that contains the last 5 characters of each string in the 'text' column.
How to extract a specific pattern from a string in a pandas dataframe?
You can use the str.extract() method in pandas to extract a specific pattern from a string in a pandas dataframe. Here's an example:
Suppose you have a pandas dataframe df with a column called text that contains strings, and you want to extract all phone numbers from these strings. You can use the following code to achieve that:
import pandas as pd
Create a sample dataframe
data = {'text': ['Call me at 123-456-7890', 'My number is 987-654-3210']} df = pd.DataFrame(data)
Extract phone numbers using regex pattern
df['phone_numbers'] = df['text'].str.extract(r'(\d{3}-\d{3}-\d{4})')
print(df)
In this code, we use the str.extract() method along with a regex pattern r'(\d{3}-\d{3}-\d{4})' to extract phone numbers in the format XXX-XXX-XXXX from the text column in the dataframe. The extracted phone numbers are stored in a new column called phone_numbers in the dataframe.
You can modify the regex pattern to extract different patterns from the strings in the dataframe based on your requirements.
How to return multiple substrings within a string in a pandas dataframe?
You can use the str.extractall method in pandas to return multiple substrings within a string in a dataframe. Here's an example:
Suppose you have a pandas dataframe called df with a column called text that contains strings with multiple substrings you want to extract. You can use the following code to extract all substrings that match a certain pattern:
import pandas as pd
Create a sample dataframe
data = {'text': ['Apple, Banana, Cherry', 'Orange, Strawberry, Pineapple']} df = pd.DataFrame(data)
Extract all substrings that match the pattern of a word starting with a capital letter
df['substrings'] = df['text'].str.extractall(r'(\b[A-Z][a-z]+\b)').groupby(level=0)[0].apply(list)
print(df)
In this example, the str.extractall method is used to extract all substrings that match the pattern of a word starting with a capital letter. The extracted substrings are then grouped by the original index and stored in a new column called substrings in the dataframe df.