Converting exponential notation numbers to strings - explanation

问题

I have DataFrame from this question:

temp=u"""Total,Price,test_num
0,71.7,2.04256e+14
1,39.5,2.04254e+14
2,82.2,2.04188e+14
3,42.9,2.04171e+14"""
df = pd.read_csv(pd.compat.StringIO(temp))

print (df)
   Total  Price      test_num
0      0   71.7  2.042560e+14
1      1   39.5  2.042540e+14
2      2   82.2  2.041880e+14
3      3   42.9  2.041710e+14

If convert floats to strings get trailing 0:

print (df['test_num'].astype('str'))
0    204256000000000.0
1    204254000000000.0
2    204188000000000.0
3    204171000000000.0
Name: test_num, dtype: object

Solution is convert floats to integer64:

print (df['test_num'].astype('int64'))
0    204256000000000
1    204254000000000
2    204188000000000
3    204171000000000
Name: test_num, dtype: int64

print (df['test_num'].astype('int64').astype(str))
0    204256000000000
1    204254000000000
2    204188000000000
3    204171000000000
Name: test_num, dtype: object

Question is why it convert this way?

I add this poor explanation, but feels it should be better:

Poor explanation:

You can check dtype of converted column - it return float64.

print (df['test_num'].dtype)
float64

After converting to string it remove exponential notation and cast to floats, so added traling 0:

print (df['test_num'].astype('str'))
0    204256000000000.0
1    204254000000000.0
2    204188000000000.0
3    204171000000000.0
Name: test_num, dtype: object

回答1:

When you use pd.read_csv to import data and do not define datatypes, pandas makes an educated guess and in this case decides, that column values like "2.04256e+14" are best represented by a float value.

This, converted back to string adds a ".0". As you corrently write, converting to int64 fixes this.

If you know that the column has int64 values only before input (and no empty values, which np.int64 cannot handle), you can force this type on import to avoid the unneeded conversions.

import numpy as np

temp=u"""Total,Price,test_num
0,71.7,2.04256e+14
1,39.5,2.04254e+14
2,82.2,2.04188e+14
3,42.9,2.04171e+14"""

df = pd.read_csv(pd.compat.StringIO(temp), dtype={2: np.int64})

print(df)

returns

   Total  Price         test_num
0      0   71.7  204256000000000
1      1   39.5  204254000000000
2      2   82.2  204188000000000
3      3   42.9  204171000000000

来源：https://stackoverflow.com/questions/51325032/converting-exponential-notation-numbers-to-strings-explanation

标签

python

pandas

casting

floating-point

integer