Engines in Python Pandas read_csv
pd.read_csv documentation notes specific differences between 'c' (default) and 'python' engines. The names indicate the language in which the parsers are written. Specifically, the docs note:
Where possible pandas uses the C parser (specified as
engine='c'), but may fall back to Python if C-unsupported options are specified.
Here are the main differences you should note (as of v0.23.4):
- 'c' is faster, while 'python' is currently more feature-complete.
skipfooter, while 'c' does not.
'python' supports flexible
sepother than a single character (inc regex), while 'c' does not.
delim_whitespace=False, which means it can auto-detect a delimiter, while 'c' does not.
float_precision, while 'python' does not (or not necessary).
dtypesupported in 'python' v0.20.0+.
delim_whitespacesupported in 'python' v0.18.1+.
Note the above may change as features are developed. You should check IO Tools (Text, CSV, HDF5, …) if you see unexpected behaviour in later versions.
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PUNEET AGARWAL about 2 months
In the document for
pd.read_csv()method in pandas in python while describing the "sep" parameter there is a mention of engines such as C engine and Python engine.
The document link is : https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html
What are these engines? What is the role of each engine? Is there any analogy which can help understand these engines better?
seralouk over 3 yearsFor a 1.2 GB csv file,
engine='python'is much faster than
c. Why is that?
jpp over 3 years@serafeim, Without your CSV file, it's difficult to tell. Perhaps there is specific content or combination or arguments where
engine='python'is more efficient. Generally, though,
'c'is more efficient while
'python'is more feature-complete.
seralouk over 3 yearsHere is the file: filebin.net/fkyil2m5yhvr1dbh any tip would be great.
ctakes forever whereas