How can i delete a row from 2D ndarray if the row contains at least one 0-CodePudding

let's say i have a dataset like this

age	id	BMI	insulin
15	0	30	0
11	30	17	30
27	15	30	0
5	21	30	45
0	21	30	45
21	21	0	45

now i want to delete the row that contains 0. I read all the data using panda now how can i delete these row from my dataset or after converting to a 2D array

CodePudding user response：

2 methods to achieve your goal:

# keep rows where all values != 0
df = df[df.ne(0).all(1)]

# or drop rows where at least one value == 0
df = df.drop(df[df.eq(0).any(1)].index)

Output:

>>> df
   age  id  BMI  insulin
1   11  30   17       30
3    5  21   30       45

CodePudding user response：

Filter rows with no 0 values per rows by compare by DataFrame.ne and DataFrame.all:

df = df[df.ne(0).all(axis=1)]

CodePudding user response：

You can loop through the dataset (I assume it's a list) and check to see if each item is 0. If it is not a zero you can add it to a new list ( a list with no 0s ). Example:

dataset = [age, id, BMI, insulin, 15, 0, 30, 0, 11, 30, 17, 30, 27, 15, 30, 0, 5, 21, 30, 45, 0, 21, 30, 45, 21, 21, 0, 45]

new_dataset = [] # new dataset which will only have values that are not zero

for data_point in dataset:
    if data_point != 0:
        new_dataset.append(data_point)
# our new dataset now contains all values from previous set without zeros