rows = df.index[[0,2]]
df.drop(rows, inplace=True)
df.drop(index='Row Name', axis=1, inplace=True)
df = df[df["column_name"].isin([0, 1, 3, 4])]
# into isin we put the value we want to mantain
df.drop(['Cochice', 'Pima'])
current table:
Modules Subjects
0 DSM020 Data programming in Python
1 DSM030 Mathematics and statistics
2 DSM040 Machine learning
3 DSM010 Big data analysis
4 DSM050 Data visualisation
5 DSM060 Data science research topics
6 DSM070 Blockchain programming
7 DSM080 Mathematics of financial markets
8 DSM110 R for data science
9 DSM120 Financial data modelling
10 DSM500 Final project
11 DSM100 Artificial
#dropping rows using indexes
list_of_subjects.drop([2,5,6,8,10,11])
output:
Modules Subjects
0 DSM020 Data programming in Python
1 DSM030 Mathematics and statistics
3 DSM010 Big data analysis
4 DSM050 Data visualisation
7 DSM080 Mathematics of financial markets
9 DSM120 Financial data modelling