How Can I Resolve UnicodeDecodeError When Reading CSV Files in Pandas?

UnicodeDecodeError: Resolving Encoding Issues When Reading CSV Files in Pandas

Introduction

Working with CSV files often presents encoding challenges, particularly when encountering characters not supported by the default encoding. Pandas, a popular data manipulation library in Python, provides the read_csv() method to import data from CSV files. However, this method can occasionally encounter the UnicodeDecodeError when dealing with Unicode-encoded characters.

Error Analysis

The provided error message indicates that the read_csv() method is struggling to decode a byte within the file using the default UTF-8 encoding. The invalid continuation byte suggests that the file may have been encoded using a different encoding.

Resolving the Issue

To resolve this error, you can explicitly specify the encoding when reading the CSV file. Pandas provides the encoding parameter for this purpose. The following approaches can be employed:

• ISO-8859-1 Encoding:
  Use the ISO-8859-1 encoding, which is commonly used for Western European character sets:

  data = pd.read_csv(filepath, encoding="ISO-8859-1")

• UTF-8 Encoding:
  Alternatively, try using UTF-8 encoding, which is suitable for worldwide character sets:

  data = pd.read_csv(filepath, encoding="utf-8")

Other aliases for ISO-8859-1, such as 'latin' or 'cp1252', can also be used. Refer to the Pandas documentation or the Python documentation for a comprehensive list of supported encodings.

Detecting File Encoding

If you are unsure about the encoding of the CSV file, you can use tools like enca, file -i on Linux, or file -I on macOS to determine the correct encoding.

Additional Resources

• [Pandas read_csv() Documentation](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html)
• [Python csv Module Examples](https://docs.python.org/3/library/csv.html#examples)
• [What Every Developer Should Know About Unicode and Character Sets](https://unicode.org/reports/tr15/)

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