dataframe
dataframe.head(3)
dataframe.tail(5)
dataframe.info()
dataframe.describe()
dataframe.coulmn_Name.unique()
dataframe['coulmn_Name']value_counts()
dataframe[dataframe.coulmn_Name=='Value'].coulmn_Name2
dataframe[(dataframe.coulmn_Name1=='Value') & (dataframe.coulmn_Name2=='Value') ]
dataframe[(dataframe.coulmn_Name1=='Value) & (dataframe.coulmn_Name2=='Value') ]['coulmn_Name1','coulmn_Name2','coulmn_Name3','coulmn_Name4']
dataframe.sort_values('coulmn_Name1', ascending=False)
dataframe[dataframe.coulmn_Name.isin(['Value1','Value2','Value3'])].coulmn_Name2
dataframe[~dataframe.coulmn_Name.isin(['Value1','Value2','Value3'])].coulmn_Name2
get_index_list =dataframe[dataframe['coulmn_Name'].isnull()].index.tolist()
for i in get_index_list:
print(dataframe.at[i,'coulmn_Name'])
المراجع -
1- https://medium.com/jbennetcodes/how-to-rewrite-your-sql-queries-in-pandas-and-more-149d341fc53e
2- https://moonbooks.org/Articles/How-to-filter-missing-data-NAN-or-NULL-values-in-a-pandas-DataFrame-/
العودة إلي مكتبة الباندا pandas library