UnicodeDecodeError, invalid continuation byte

I had the same error when I tried to open a CSV file by pandas.read_csv method.

The solution was change the encoding to latin-1:

pd.read_csv('ml-100k/u.item', sep='|', names=m_cols , encoding='latin-1')

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In binary, 0xE9 looks like 1110 1001. If you read about UTF-8 on Wikipedia, you’ll see that such a byte must be followed by two of the form 10xx xxxx. So, for example:

>>> b'\xe9\x80\x80'.decode('utf-8')
u'\u9000'

But that’s just the mechanical cause of the exception. In this case, you have a string that is almost certainly encoded in latin 1. You can see how UTF-8 and latin 1 look different:

>>> u'\xe9'.encode('utf-8')
b'\xc3\xa9'
>>> u'\xe9'.encode('latin-1')
b'\xe9'

(Note, I'm using a mix of Python 2 and 3 representation here. The input is valid in any version of Python, but your Python interpreter is unlikely to actually show both unicode and byte strings in this way.)

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It is invalid UTF-8. That character is the e-acute character in ISO-Latin1, which is why it succeeds with that codeset.

If you don't know the codeset you're receiving strings in, you're in a bit of trouble. It would be best if a single codeset (hopefully UTF-8) would be chosen for your protocol/application and then you'd just reject ones that didn't decode.

If you can't do that, you'll need heuristics.

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Because UTF-8 is multibyte and there is no char corresponding to your combination of \xe9 plus following space.

Why should it succeed in both utf-8 and latin-1?

Here how the same sentence should be in utf-8:

>>> o.decode('latin-1').encode("utf-8")
'a test of \xc3\xa9 char'

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If this error arises when manipulating a file that was just opened, check to see if you opened it in 'rb' mode

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Use this, If it shows the error of UTF-8

pd.read_csv('File_name.csv',encoding='latin-1')

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utf-8 code error usually comes when the range of numeric values exceeding 0 to 127.

the reason to raise this exception is:

1)If the code point is < 128, each byte is the same as the value of the code point. 2)If the code point is 128 or greater, the Unicode string can’t be represented in this encoding. (Python raises a UnicodeEncodeError exception in this case.)

In order to to overcome this we have a set of encodings, the most widely used is "Latin-1, also known as ISO-8859-1"

So ISO-8859-1 Unicode points 0–255 are identical to the Latin-1 values, so converting to this encoding simply requires converting code points to byte values; if a code point larger than 255 is encountered, the string can’t be encoded into Latin-1

when this exception occurs when you are trying to load a data set ,try using this format

df=pd.read_csv("top50.csv",encoding='ISO-8859-1')

Add encoding technique at the end of the syntax which then accepts to load the data set.

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Well this type of error comes when u are taking input a particular file or data in pandas such as :-

data=pd.read_csv('/kaggle/input/fertilizers-by-product-fao/FertilizersProduct.csv)

Then the error is displaying like this :- UnicodeDecodeError: 'utf-8' codec can't decode byte 0xf4 in position 1: invalid continuation byte

So to avoid this type of error can be removed by adding an argument

data=pd.read_csv('/kaggle/input/fertilizers-by-product-fao/FertilizersProduct.csv', encoding='ISO-8859-1')

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This happened to me also, while i was reading text containing Hebrew from a .txt file.

I clicked: file -> save as and I saved this file as a UTF-8 encoding

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In this case, I tried to execute a .py which active a path/file.sql.

My solution was to modify the codification of the file.sql to "UTF-8 without BOM" and it works!

You can do it with Notepad++.

i will leave a part of my code.

con = psycopg2.connect(host = sys.argv[1],
port = sys.argv[2],dbname = sys.argv[3],user = sys.argv[4], password = sys.argv[5])

cursor = con.cursor()
sqlfile = open(path, 'r')

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TLDR: I would recommend investigating the source of the problem in depth before switching encoders to silence the error.

I got this error as I was processing a large number of zip files with additional zip files in them.

My workflow was the following:

Read zip Read child zip Read text from child zip

At some point I was hitting the encoding error above. Upon closer inspection, it turned out that some child zips erroneously contained further zips. Reading these zips as text lead to some funky character representation that I could silence with encoding="latin-1", but which in turn caused issues further down the line. Since I was working with international data it was not completely foolish to assume it was an encoding problem (I had problems with 0xc2: Â), but in the end it was not the actual issue.

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The solution was change to "UTF-8 sin BOM"

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