save df to txt
df.to_csv(r'c:datapandas.txt', header=None, index=None, sep='t', mode='a')save df to txt
df.to_csv(r'c:datapandas.txt', header=None, index=None, sep='t', mode='a')pandas go through csv file
data = pd.read_csv(
"data/files/complex_data_example.tsv", # relative python path to subdirectory
sep='t' # Tab-separated value file.
quotechar="'", # single quote allowed as quote character
dtype={"salary": int}, # Parse the salary column as an integer
usecols=['name', 'birth_date', 'salary']. # Only load the three columns specified.
parse_dates=['birth_date'], # Intepret the birth_date column as a date
skiprows=10, # Skip the first 10 rows of the file
na_values=['.', '??'] # Take any '.' or '??' values as NA
)Copyright © 2021 Codeinu
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