CODEWITHSUNDEEP
pythonpandas
jhaywoo8
jhaywoo8

Reputation: 767

Drop a list of rows from Pandas df

I've created a loop to get a list of rows to drop. 

cols = []
for i in range(len(df)):
    if i != len(df)-1:
        if (df['Player'][i] == df['Player'][i+1]):
            cols.append(i+1)

Now I want to go through cols and drop each row by its number. I've tried using the following loop to drop these rows but it's not working.

for col in cols:
    df.drop([[col]])

Upvotes: 0

Views: 1832

Answers (3)

Ken Wei
Ken Wei

Reputation: 3130

It looks like you are trying to get rid of rows preceded by a duplicate value of Player. With pandas, always try to work with vectorization: df.Player == df.Player.shift() checks whether each entry in Player is equal to the last, so a one-line solution is

df[df.Player != df.Player.shift()]

Upvotes: 0

xudesheng
xudesheng

Reputation: 1102

if you just want to delete rows with duplicated value in col 'Player', you can:

df.drop_duplicates(subset=['Player'],inplace=True)

Upvotes: 0

Alex Fung
Alex Fung

Reputation: 2006

For dropping rows:

df.drop(rows,inplace=True)

For dropping columns:

df.drop(cols,axis=1,inplace=True)

Test: 

df = pd.DataFrame({'A':[1,2,3,4,5],'B':[1,2,3,4,5]})
print('DataFrame with initialised :\n',df,'\n')
df.drop([2,4],inplace=True)
print('DataFrame after dropping 2 rows:\n',df,'\n')
df.drop(['B'],axis=1,inplace=True)
print('DataFrame after dropping 1 column:\n',df,'\n')

Output:

DataFrame with initialised :
   A  B
0  1  1
1  2  2
2  3  3
3  4  4
4  5  5 

DataFrame after dropping 2 rows:
   A  B
0  1  1
1  2  2
3  4  4 

DataFrame after dropping 1 column:
   A
0  1
1  2
3  4

Upvotes: 1

Related Questions