How can I create a Pandas DataFrame from a text file with a specific structure that includes state and region patterns?

Reading and Shaping Pandas DataFrame from Text File with State and Region Patterns

Creating a Pandas DataFrame from a text file with a specific structure requires strategic data manipulation. Let's delve into the problem and explore a solution to transform the provided text into the desired DataFrame.

Data Structure

The text file follows a hierarchical structure where:

• Rows with "[edit]" are state names.
• Rows with "[number]" are region names.
• Region names should be repeated for the same state.

Solution

1. Reading the Text File

First, read the text file and create a DataFrame using read_csv(). Since there are no specific delimiters, specify a custom separator that does not exist in the data, such as a semicolon:

<code class="python">df = pd.read_csv('filename.txt', sep=";", names=['Region Name'])</code>

2. Extracting State Names

Identify the rows containing state names using the str.extract() method and regular expressions to capture the state name up to "[edit]". Create a new column called 'State' with these values:

<code class="python">df.insert(0, 'State', df['Region Name'].str.extract('(.*)\[edit\]', expand=False).ffill())</code>

3. Removing Bracket Information from Region Names

Remove the brackets and any characters enclosed within them from the 'Region Name' column:

<code class="python">df['Region Name'] = df['Region Name'].str.replace(r' \(.+$', '')</code>

4. Removing State Header Rows

Delete the rows where "[edit]" appears in the 'Region Name' column. Create a mask using str.contains():

<code class="python">df = df[~df['Region Name'].str.contains('\[edit\]')].reset_index(drop=True)</code>

5. Final DataFrame

At this point, you have a DataFrame with the 'State' and 'Region Name' columns, as required.

<code class="python">print(df)</code>

Extended Solution

If you prefer to include the bracketed text in the 'Region Name' column, here is a modified solution:

<code class="python">df.insert(0, 'State', df['Region Name'].str.extract('(.*)\[edit\]', expand=False).ffill())
df = df[~df['Region Name'].str.contains('\[edit\]')].reset_index(drop=True)

print(df)</code>

This will produce a DataFrame with 'State' and 'Region Name' columns, where the region names include the bracketed text.

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