<jupyter_start><jupyter_text>1) Pandas read_csv na_values 2) Pandas read_csv keep_default_na 3) Pandas read_csv na_filter<jupyter_code>import pandas as pd
df=pd.read_csv('csv_files/Fortune_10.csv')
df
# NaN stand for Not a Number
# #na null is also consider NaN
import pandas as pd
df=pd.read_csv('csv_files/Fortune_10.csv',na_values=['not available','no values'])
df

df=pd.read_csv('csv_files/Fortune_10.csv',na_values={'Companies':'no values','Growth':'not available'})
df
df=pd.read_csv('csv_files/Fortune_10.csv',keep_default_na=True)
df
# to improve speed of pandas to not look for empty cell use na_filter=False
df=pd.read_csv('csv_files/Fortune_10.csv',na_filter=False)
df<jupyter_output><empty_output>
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