load csv file using pandas
import pandas as pd
df = pd.read_csv (r'Path where the CSV file is storedFile name.csv')
print (df)load csv file using pandas
import pandas as pd
df = pd.read_csv (r'Path where the CSV file is storedFile name.csv')
print (df)csv file in dataframe
import pandas as pddf = pd.read_csv ('file_name.csv')print(df)pandas read csv
import pandas as pd
cereal_df = pd.read_csv("/tmp/tmp07wuam09/data/cereal.csv")
cereal_df2 = pd.read_csv("data/cereal.csv")
# Are they the same?
print(pd.DataFrame.equals(cereal_df, cereal_df2))read a csv file in pandas
you should be in the same dir as .py file
df = pd.read_csv('your_file_name.csv')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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