Question

For the given table, write a code in python to delete the row if the row has more than 70% of it's values as 0 or Nan

In the table there are 11 values in a row without considering ID and Name, so if there more than 7 values are null values then the row should be deleted.

**code should be in python using pandas library

ID	Name	a	b	c	d	e	f	g	h	i	j	k
7	gg	0.214	0.111	-0.151	0.151	0.176	0.345	-0.073	0.176	0.151	0.111	0.202
8	hh							-0.119
10	jj		-1.473	0.124	-0.62		0.322	0.029	-1.088
11	kk	-0.76		0.465			0.454	-0.073
12	ll						0.546		-0.493
13	mm	0.189	-1.028	-0.534	0.202	0.029	0.848
15	oo	0.07		0.731			0.322	0.176	-1.183	-0.251

Answer 1

import pandas as pd
df = pd.read_csv('C:\\Users\\flash\\Desktop\\sample.csv')
print(df)
mod = df;
count_nan = df.isnull().sum(axis=1) # count NaN value row wise
for i in range(count_nan.shape[0]):
    if (((count_nan[i])*100)/13) > 70:   # checking % Nan
        mod = df.drop(df.index[i])       # modified after delete a row
        print(mod)

Output:

end