df.drop(df.index[-2])
df.drop(df.index[[3, 4]])
df.drop(['row_1', 'row_2'])
df.drop('column_1', axis=1)
df[df.name != 'cell']
df.reset_index()
# delete a single row by index value 0
data = data.drop(labels=0, axis=0)
# delete a few specified rows at index values 0, 15, 20.
# Note that the index values do not always align to row numbers.
data = data.drop(labels=[1,15,20], axis=0)
# delete a range of rows - index values 10-20
data = data.drop(labels=range(40, 45), axis=0)
# The labels parameter name can be omitted, and axis is 0 by default
# Shorter versions of the above:
data = data.drop(0)
data = data.drop([0, 15, 20])
data = data.drop(range(10,20))<div class="open_grepper_editor" title="Edit & Save To Grepper"></div>
df.drop(df.index[2])
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