Zeile aus DataFrame Python löschen
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']
JJSSEECC
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.drop(df.index[2])df = df.drop(df.columns[[0, 1, 3]], axis=1) # df.columns is zero-based pd.Index df = df[df["column_name"].isin([0, 1, 3, 4])]
# into isin we put the value we want to mantain#to drop by column number instead of by column label, try this to delete, e.g. the 1st, 2nd and 4th columns
df = df.drop(df.columns[[0, 1, 3]], axis=1) # df.columns is zero-based pd.Index 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