Deleting DataFrame row in Pandas based on column value

Question

I have the following DataFrame:

             daysago  line_race rating        rw    wrating
 line_date                                                 
 2007         


        

Answer 1

I compiled and run my code. This is accurate code. You can try it your own.

data = pd.read_excel('file.xlsx')

If you have any special character or space in column name you can write it in '' like in the given code:

data = data[data['expire/t'].notnull()]
print (date)

If there is just a single string column name without any space or special character you can directly access it.

data = data[data.expire ! = 0]
print (date)

Answer 2

Just adding another way for DataFrame expanded over all columns:

for column in df.columns:
   df = df[df[column]!=0]

Example:

def z_score(data,count):
   threshold=3
   for column in data.columns:
       mean = np.mean(data[column])
       std = np.std(data[column])
       for i in data[column]:
           zscore = (i-mean)/std
           if(np.abs(zscore)>threshold):
               count=count+1
               data = data[data[column]!=i]
   return data,count

Answer 3

just to add another solution, particularly useful if you are using the new pandas assessors, other solutions will replace the original pandas and lose the assessors

df.drop(df.loc[df['line_race']==0].index, inplace=True)

Answer 4

If I'm understanding correctly, it should be as simple as:

df = df[df.line_race != 0]