Modifying values in a dataframe

Question

I am trying to iterate through the rows of a dataframe and modify some values as I iterate. The dataframe looks like this:

     Time WindSpeed        SkyCover   Temp  DewPt   RH   Press  Precip
3   21:53      11       Light Snow   -1.7   -6.1  72%  1003.1       0
4   20:53    N 11    Mostly Cloudy   -2.2   -6.1  75%  1002.8       0
5   19:53    Calm    Mostly Cloudy   -2.8   -6.7  75%  1002.7       0
6   18:53    Calm         Overcast   -1.7   -6.7  69%  1002.4       0
7   17:53     N 5         Overcast   -1.7   -7.2  66%  1002.6       0
8   16:53    NE 8         Overcast   -1.1   -7.2  64%  1002.5       0
…

I have written the following loop to go through the dataframe and alter the windspeed column. This column is a vector when windspeed is greater than 1 KPH and a text value 'Calm' when below that threshold. I am wanting this loop to look at the column values row by row and if it is calm, put '1' in its place but if it is greater than one, remove the direction and keep only the scalar value.

for i in df.index:
    if df.at[i, 2] == 'Calm': 
        df.at[i, 2] = 1
    else:
        df.at[i, 2] = re.findall('[0-9]+', df.at[i, 2])[0]

As you can see in the above dataframe, this loop has worked on the first row of data but does not continue past that. I am not receiving any error messages as to why it is stopping after the first row.

meW · Accepted Answer · 2018-12-27 07:19:24Z

3

Use apply:

df.WindSpeed = df.WindSpeed.apply(lambda x: 1 if x == 'Calm' else re.findall(r'[0-9]+',x)[0])

answered Dec 27, 2018 at 7:19

meW

3,97711 silver badges27 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

Ankur Sinha · Accepted Answer · 2018-12-27 07:34:18Z

1

Adding another way of doing it:

import numpy as np

df['WindSpeed'] = np.where(df['WindSpeed'] == 'Calm', '1', df['WindSpeed'].str.extract('(\d+)'))

answered Dec 27, 2018 at 7:34

Ankur Sinha

6,6648 gold badges44 silver badges74 bronze badges

Comments

meW · Accepted Answer · 2018-12-27 08:33:07Z

0

df['WindSpeed']=df['WindSpeed'].apply(modify)

def modify(x):
       if x=='Calm' :
                    y=1;
       else: 
                    y=re.findall('[0-9]+',x)

       return y

edited Dec 27, 2018 at 8:33

meW

3,97711 silver badges27 bronze badges

answered Dec 27, 2018 at 7:25

ColdSteel

335 bronze badges

1 Comment

ColdSteel Over a year ago

meW's answer is better with lambda functions. Also sorry for bad formatting first answer here

Collectives™ on Stack Overflow

Modifying values in a dataframe

3 Answers 3

Comments

Comments

1 Comment

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

3 Answers 3

Comments

Comments

1 Comment

Your Answer

Sign up or log in

Post as a guest

Related