Using pandas, how to use dataframe to find a column value if another column is not null?

Question

I have a csv file bellow:

df.csv

Symbol  Total Volume (on 01/17/2018)
A   
B   
C       1.900
D   
E   
F   
G       1.051

I would like to find the Symbols if the Total Volume (on 01/17/2018) value is not null. In another words, I would like to retung "G", in this case.

I was tryng to do it with those lines of code:

df = pd.read_csv('./df.csv')
type_filter = df[df['Total'].str.match('', case=False)]
    a = type_filter['Symbol']
print type_filter

Any ideas?

By the way, could you also give me an example if I would like to find the Symbols if the Total value is null?

df.Symbol[df.Total.str.strip().ne('')] And for the inverse, invert the condition with ~. — cs95
– cs95, Commented Jan 21, 2018 at 10:56
I've edited the question, could you check it again, and see if this works? — rafasalo
– rafasalo, Commented Jan 21, 2018 at 11:00

cs95 · Accepted Answer · 2018-01-21 11:34:07Z

1

You can use str.strip with a not equals comparison with ne, and use the resultant mask to index df -

df

  Symbol Total Volume
0      A             
1      B             
2      C        1.900
3      D             
4      E             
5      F             
6      G        1.051

df.loc[df['Total Volume'].str.strip().ne(''), 'Symbol']

Or, if you have a numeric column with NaNs -

df.loc[df['Total Volume'].notnull(), 'Symbol']

2    C
6    G
Name: Symbol, dtype: object

edited Jan 21, 2018 at 11:34

answered Jan 21, 2018 at 11:04

cs95

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12 Comments

rafasalo Over a year ago

it is returning this: AttributeError: Can only use .str accessor with string values, which use np.object_ dtype in pandas

rafasalo Over a year ago

BTW, when I print(df) the empty cells return "NaN"

rafasalo Over a year ago

What if I would like to look in two columns, what should I do?

cs95 Over a year ago

@rafasalo df.loc[df['Total Volume'].notnull(), ['col1', 'col2']]

rafasalo Over a year ago

Sorry, I didn't explain right. If I have a third column. Like: Symbol, Total Volume and Percentage, and I want to look at notnull() in Total Volume and Percentage?

|

Pang · Accepted Answer · 2018-01-22 02:36:21Z

0

I found how:

df = pd.read_csv('./df.csv')
type_filter = df[df['Total'].notnull()]
a = type_filter['Symbol']
print type_filter

edited Jan 22, 2018 at 2:36

Pang

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answered Jan 21, 2018 at 11:42

rafasalo

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