I have string column in my df table, like this below:

d = {'col1': ['1.2', '3.4', '1.99', '0.14', '2.9', '', '2.3']}
df = pd.DataFrame(data=d)
df

I would like to convert this column, so that all values ​​contain two decimal places, but without changing the type of this column to numeric type.

Expected output - a string column with values:

I am a little new to Python, I tried padding 0 How to pad a numeric string with zeros to the right in Python? depending on the length of the value in the column, but it actually didn't work.

Do you have idea how to handle it?

CodePudding user response：

Use str.ljust:

df['col1'] = df['col1'].str.ljust(4, '0')

output:

   col1
0  1.20
1  3.40
2  1.99
3  0.14
4  2.90
5  2.30

To leave empty rows intact:

df['col1'] = df['col1'].mask(df['col1'].astype(bool), df['col1'].str.ljust(4, '0'))

output:

   col1
0  1.20
1  3.40
2  1.99
3  0.14
4  2.90
5      
6  2.30

NB. to get the max string length: df['col1'].str.len().max() -> 4

CodePudding user response：

Like this:

df['col1'] = df['col1'].astype(float).map('{:,.2f}'.format).astype(str)

If you have '' in this column you better replace them before to '0'.

CodePudding user response：

This one will work no matter how many columns are in your dictionary. Try this:

d = {'col1': ['1.2', '3.4', '1.99', '0.14', '2.9' '', '2.3']}
for x in d:
  for y in range(0,len(d[x])):
    d[x][y]=d[x][y].ljust(4,"0")
print(d)

CodePudding user response：

You can easily use the round or format function. In your specific case, using format, you can write something like this:

d = ['1.2', '3.4', '1.99', '0.14', '2.9', '', '2.3']
for i in range(len(d)):
     if d[i] == '':
          d[i] = '0'    
     d[i] = "{:.2f}".format(float(d[i]))
print ('col1', d)

output:

'col1', ['1.20', '3.40', '1.99', '0.14', '2.90', '0.00', '2.30']