Python Pandas Dataframe convert String column to Float while Keeping Precision (decimal places)

Question

when I convert a column from string to float I lose decimal places, is there a clear way how to keep decimal places?

dicti = {'1': ['55.230530663425',
  '43.597357785755'],
 '2': ['25.231784186637',
  '93.59759890623'],
 '3': ['75.229467797447',
  '33.597732846763'],
 '4': ['15.228959922301',
  '33.596897400263'],
 '5': ['95.231278845519',
  '23.599502230125']}


df = pd.DataFrame.from_dict(dicti, 'index')
df[0] = df[0].astype(float)
df[1] = df[1].astype(float)
print(df)

           0          1
1  55.230531  43.597358
2  25.231784  93.597599
3  75.229468  33.597733
4  15.228960  33.596897
5  95.231279  23.599502

they are kept, just not printed out

anon01
– anon01

2022-01-19 23:41:45 +00:00
Commented Jan 19, 2022 at 23:41 — anon01
– anon01, Commented Jan 19, 2022 at 23:41

RustyPython · Accepted Answer · 2022-01-19 23:52:08Z

1

Check out the top answer from

Pandas data precision

to see how to change the display precision if you want to see more decimal places. As has been said, the full precision is stored, just not displayed.

answered Jan 19, 2022 at 23:52

RustyPython

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