I\'m trying to read the data from .sas7bdat format of SAS using pandas function read_sas:
import pandas as pd
df = pd.read_sas(\'D:/input/houses.sas7bdat\', form
The encoding
argument in pd.read_sas()
leads me to have very large dataframes which lead me to have memory related errors.
An other way to deal with the problem would be to convert
the byte strings to an other encoding (e.g. utf8
).
Example dataframe:
df = pd.DataFrame({"A": [1, 2, 3],
"B": [b"a", b"b", b"c"],
"C": ["a", "b", "c"]})
Transform byte strings to strings:
for col in df:
if isinstance(df[col][0], bytes):
print(col, "will be transformed from bytestring to string")
df[col] = df[col].str.decode("utf8") # or any other encoding
print(df)
output:
A B C
0 1 a a
1 2 b b
2 3 c c
Useful links:
Pandas Series.str.decode() page of GeeksforGeeks (where I found my solution)
What is the difference between a string and a byte string?