Read CSV files using PIPE delimiter

1.How to update,read CSV files with pipe delimiter

  1. how to merge two files using pipe delimiter

Reading CSV Files with Pipe Delimiter:

To read a CSV file with a pipe (|) delimiter, you can use the pandas library in Python. Here’s an example:

import pandas as pd

Read the CSV file with a pipe delimiter

df = pd.read_csv(‘filename.csv’, delimiter=‘|’)

This code will read the file named ‘filename.csv’ and interpret the pipe character as the delimiter, properly parsing the data into a DataFrame.

Updating CSV Files with Pipe Delimiter:

To update a DataFrame and save it as a CSV file with a pipe delimiter, you can use the following code:

Update the DataFrame by adding a new column

df[‘new_column’] = ‘new_value’

Save the updated DataFrame as a CSV file with a pipe delimiter

df.to_csv(‘updated_filename.csv’, sep=‘|’, index=False)

Update the DataFrame by adding a new column

df[‘new_column’] = ‘new_value’

Save the updated DataFrame as a CSV file with a pipe delimiter

df.to_csv(‘updated_filename.csv’, sep=‘|’, index=False)

In this code, a new column named ‘new_column’ is added to the DataFrame, and all the rows are populated with the value ‘new_value’. Then, the modified DataFrame is saved as a CSV file named ‘updated_filename.csv’ using the pipe delimiter.

Merging Two Files Using Pipe Delimiter:

To merge two CSV files with a pipe delimiter, you can use the pandas library. Here’s an example:

import pandas as pd

Read the first CSV file with a pipe delimiter

df1 = pd.read_csv(‘file1.csv’, delimiter=‘|’)

Read the second CSV file with a pipe delimiter

df2 = pd.read_csv(‘file2.csv’, delimiter=‘|’)

Merge the two DataFrames based on a common column

merged_df = pd.merge(df1, df2, on=‘common_column’)

Save the merged DataFrame as a CSV file with a pipe delimiter

merged_df.to_csv(‘merged_file.csv’, sep=‘|’, index=False)

In this code, two CSV files (‘file1.csv’ and ‘file2.csv’) are read into separate DataFrames (df1 and df2 ) using the pipe delimiter. The two DataFrames are then merged based on a common column using the pd.merge function. Finally, the merged DataFrame is saved as a CSV file named ‘merged_file.csv’ using the pipe delimiter.