Read csv without filling up empty values

Question

I have the following csv I want to read into Python (Spyder) and count the amount of blank values in column 2:

column 1	column 2
A	N/A
B	N/A
C	N/A
D
E	N/A
F	N/A
G
H	N/A

In this case, there are two blank values, the rest are default values.

The standard code is:

LoadFile=pd.read_csv(FileName)

Which reads in the data as:

column 1	column 2
A	NaN
B	NaN
C	NaN
D	NaN
E	NaN
F	NaN
G	NaN
H	NaN

So the empty count is 8, not 2

missings =LoadFile['column 2'].isnull().sum()

Then I tried to read it in as:

LoadFile=pd.read_csv(FileName,na_values='', keep_default_na=False)

Which changes the table into:

column 1	column 2
A	N/A
B	N/A
C	N/A
D	N/A
E	N/A
F	N/A
G	N/A
H	N/A

So the empty count is zero.

How do I read in my csv file so the empty count is 2 and it does not alter the empty values.

A csv file is a text file. Instead of showing the obtained dataframe, you should show the raw content of the file. — Serge Ballesta
– Serge Ballesta, Commented Sep 11, 2024 at 9:39

mozway · Accepted Answer · 2024-09-11 09:38:57Z

0

This works fine for me.

CSV = '''column 1,column 2
A,N/A
B,N/A
C,N/A
D,
E,N/A
F,N/A
G,
H,N/A'''

df = pd.read_csv(io.StringIO(CSV), na_values='', keep_default_na=False)
df['column 2'].isnull().sum()
# 2

Alternatively, don't define na_values and count the blanks:

df = pd.read_csv(FileName, keep_default_na=False)
missings = df['column 2'].eq('').sum()

Output: 2

answered Sep 11, 2024 at 9:38

mozway

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1 Comment

Jellyse Over a year ago

Not defining na_values worked.

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