how to delete whitespace from nd array python

Question

I have yearly data sets with some missing data. I used this code to read but unable to omit white space present at the end of february. can anyone help to solve this problem?

df1 = pd.read_fwf('DQ404.7_77.txt',widths=ws,header=9, nrows=31, keep_default_na = False)
df1 = df1.drop('Day', 1)
df2 = np.array(df1).T

what I want is to arrange all the data in one column with respect to date. My data is uploaded in this link you can download https://drive.google.com/open?id=0B2rkXkOkG7ExbEVwZUpHR29LNFE

what i wanted is to get time series data from this file and it should be like

Feb,25  13
Feb,26  13
Feb,27  13
Feb,28  13
March, 1    10
March, 2    10
March, 3    10

Not with empty strings in between february and March

Sorry are you asking how to remove rows where the entries are NaN or empty strings ''? — EdChum
– EdChum, Commented May 13, 2016 at 8:39
You've not included the definition for ws so your code is not runnable — EdChum
– EdChum, Commented May 13, 2016 at 8:40
@ EdChum no no I have defination of ws, and wanted to remove empty strings . and I have defined ws = [4,9,7,7,7,7,7,7,7,7,7,7,7] — bikuser
– bikuser, Commented May 13, 2016 at 8:46
So you want to drop the rows or replace empty strings with NaN? — EdChum
– EdChum, Commented May 13, 2016 at 8:49
hello EdChum, I want to drop empty strings, so that when I stack it should be regular — bikuser
– bikuser, Commented May 13, 2016 at 8:50

EdChum · Accepted Answer · 2016-05-13 09:41:32Z

2

So after a lot of comments it looks like df[df != ''] works for you

edited May 13, 2016 at 9:41

answered May 13, 2016 at 8:51

EdChum

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11 Comments

bikuser Over a year ago

then we will miss the values from Jan and from other month...isn't it?

EdChum Over a year ago

I asked you what you wanted you stated I want to drop empty strings, so that when I stack it should be regular dropping doesn't equal replacement so you've not explained clear enough what you want. So I ask again what do you want instead of empty strings? Do you want NaN or you want to forward fill from the last valid value?

bikuser Over a year ago

sorry for not making it clear but , I want to forward fill from the last valid value

EdChum Over a year ago

What about the other 'NA' values do you want these to be treated as NaN and forward filled?

EdChum Over a year ago

So I ask again what was wrong with df[df['Feb.' != '']? or df[df != '']? and no it was not clear

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