I have tried to delete blank rows from my cvs file, however this is not working, it only writes out the first line
please take a look and tell me how i can get all the rows with text and skip the rows that are blank
Here is the code:
I just reads out the first line of the csv file
Thank you in advance!
First read your csv file with pandas with
df=pd.read_csv('input.csv')
then remove blank rows,
df=df.dropna()
For more details in dropna, check the documentation.
There is problem:
for line in df:
print (line)
return columns names.
If I have a csv file like below with blank row
B;D;K;N;M;R 0;2017-04-27 01:35:30;C;3.5;A;01:15:00;23.0 1;2017-04-27 01:37:30;B;3.5;B;01:13:00;24.0 2;2017-04-27 01:39:00;K;3.5;C;00:02:00;99.0 4;2017-04-27 01:39:00;K;3.5;C;00:02:00;99.0
df = pd.read_csv('input.csv',delimiter=';') will give the dataframe ignoring the blank lines.
B D K N M R 0 2017-04-27 01:35:30 C 3.5 A 01:15:00 23.0 1 2017-04-27 01:37:30 B 3.5 B 01:13:00 24.0 2 2017-04-27 01:39:00 K 3.5 C 00:02:00 99.0 4 2017-04-27 01:39:00 K 3.5 C 00:02:00 99.0
Your code works when you use open. Pandas read_csv will convert the csv file into dataframe. You might be confused with one another.
df = open('input.csv')
new_contents = []
for line in df:
if not line.strip():
continue
else:
new_contents.append(line)
With the latest pandas (v 1.3.0), there is an argument where you can tell it to skip blank rows. It's enabled by default, but if you want to make it True anyway (e.g. self-documenting code), just set that flag to True. This is from the doc: https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html
skip_blank_lines: bool, default True
If True, skip over blank lines rather than interpreting as NaN values.
So, in your code it is:
df = pd.read_csv(path, sep = ';', skip_blank_lines=True)
df.read_csv(...).dropna()