Pandas: remove empty strings from dataframe

Question

I have dataframe

id    m1    m2    m3
111   20    0     12
222   0     0     0
333   3     1     18

I need to get only

id    m1    m2    m3
111   20    0     12
333   3     1     18

I use

df.drop(axis=0, how='all')

But it returns me full dataframe. How can I fix that?

I thought its dropna sorry. You can do that without using drop. Check if my answer helps — Bharath M Shetty
– Bharath M Shetty, Commented Oct 6, 2017 at 14:20

Bharath M Shetty · Accepted Answer · 2017-10-06 14:19:47Z

4

You can use boolean indexing i.e

ndf = df[~(df.set_index('id')==0).all(1).values]

Output:

   id  m1  m2  m3
0  111  20   0  12
2  333   3   1  18

answered Oct 6, 2017 at 14:19

Bharath M Shetty

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MaxU - stand with Ukraine · Accepted Answer · 2017-10-06 14:30:53Z

4

In [91]: ndf = df[df.filter(regex='^m').astype(bool).any(1)]

In [92]: ndf
Out[92]:
    id  m1  m2  m3
0  111  20   0  12
2  333   3   1  18

answered Oct 6, 2017 at 14:30

MaxU - stand with Ukraine

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4 Comments

Bharath M Shetty Over a year ago

whats ^m I'm new to that pattern?

Vaishali Over a year ago

Very smart, took me a sec to figure out astyp(bool) here :)

MaxU - stand with Ukraine Over a year ago

@Bharathshetty, it's a RegEx - meaning string that starts with "m"

Bharath M Shetty Over a year ago

Oh shit I imagined an escape character behind m I thought its like ^\m. My bad I feel stupid now haha

Priya G · Accepted Answer · 2018-12-13 11:09:14Z

0

here,it can be done in simple way as follows.

df=df[df['id']!=222]

print(df)

id m1 m2 m3 0 111 20 0 12 2 333 3 1 18

edited Dec 13, 2018 at 11:09

answered Dec 13, 2018 at 10:52

Priya G

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