Drop row in pandas dataframe if any value in the row equals zero
Question:
How do I drop a row if any of the values in the row equal zero?
I would normally use df.dropna() for NaN values but not sure how to do it with “0” values.
Answers:
i think the easiest way is looking at rows where all values are not equal to 0 and assign result to df:
df = df[(df != 0).all(1)]
You could make a boolean frame and then use any:
>>> df = pd.DataFrame([[1,0,2],[1,2,3],[0,1,2],[4,5,6]])
>>> df
0 1 2
0 1 0 2
1 1 2 3
2 0 1 2
3 4 5 6
>>> df == 0
0 1 2
0 False True False
1 False False False
2 True False False
3 False False False
>>> df = df[~(df == 0).any(axis=1)]
>>> df
0 1 2
1 1 2 3
3 4 5 6
Assume a simple DataFrame as below:
df=pd.DataFrame([1,2,0,3,4,0,9])
Pick non-zero values which turns all zero values into nan and remove nan-values
df=df[df!=0].dropna()
df
Output:
0
0 1.0
1 2.0
3 3.0
4 4.0
6 9.0
Although it is late, someone else might find it helpful.
I had similar issue. But the following worked best for me.
df =pd.read_csv(r'your file')
df =df[df['your column name'] !=0]
reference:
Drop rows with all zeros in pandas data frame
see @ikbel benabdessamad
How do I drop a row if any of the values in the row equal zero?
I would normally use df.dropna() for NaN values but not sure how to do it with “0” values.
i think the easiest way is looking at rows where all values are not equal to 0 and assign result to df:
df = df[(df != 0).all(1)]
You could make a boolean frame and then use any:
>>> df = pd.DataFrame([[1,0,2],[1,2,3],[0,1,2],[4,5,6]])
>>> df
0 1 2
0 1 0 2
1 1 2 3
2 0 1 2
3 4 5 6
>>> df == 0
0 1 2
0 False True False
1 False False False
2 True False False
3 False False False
>>> df = df[~(df == 0).any(axis=1)]
>>> df
0 1 2
1 1 2 3
3 4 5 6
Assume a simple DataFrame as below:
df=pd.DataFrame([1,2,0,3,4,0,9])
Pick non-zero values which turns all zero values into nan and remove nan-values
df=df[df!=0].dropna()
df
Output:
0
0 1.0
1 2.0
3 3.0
4 4.0
6 9.0
Although it is late, someone else might find it helpful.
I had similar issue. But the following worked best for me.
df =pd.read_csv(r'your file')
df =df[df['your column name'] !=0]
reference:
Drop rows with all zeros in pandas data frame
see @ikbel benabdessamad