print_hundredths

print hundredths

print hundredths

Let's define hundredths as numbers with two decimal digits. This can be money amounts in dollars and cents.

tags | pennies, dollar-cent amounts, print two digits after decimal

write single numbers

There are two possible ways - round, format expression. I prefer the format expression as it always gives the same number of digits after the decimal.

	round	format
output type	float	string
output type	In [1]: a = 10.30467 In [2]: type(round(a,2)) Out[2]: float In [3]: type('{:.2f}'.format(a)) Out[3]: str
number of digits after the decimal point	varies	always two
number of digits after the decimal point	In [4]: a = 10.30467 In [5]: round(a,2) Out[5]: 10.3 In [6]: '{:.2f}'.format(a) Out[6]: '10.30'

Tested with | Python 3.10.9, ipython 8.8.0

tags | round vs. format

write dataframe to csv files

If you round and dump the data into a csv file, it does not align around the decimal point. The result is also difficult to align using command line tools.

On the other hand, if the data is formatted using the format expression, it will still not align but can be aligned using command line tools.

For example, consider

$ ipython
Python 3.10.9 | packaged by conda-forge | (main, Jan 11 2023, 15:15:40) [MSC v.1916 64 bit (AMD64)]
Type 'copyright', 'credits' or 'license' for more information
IPython 8.8.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]:
import pandas as pd
df = pd.DataFrame({
  'symbol': ['A', 'B', 'C', 'D'],
  'price': [8.222, 7.007, 3.971, 9.801],
  'change': [6.601, 7.241, -9.341, 48.001]})
df
Out[1]:
  symbol  price  change
0      A  8.222   6.601
1      B  7.007   7.241
2      C  3.971  -9.341
3      D  9.801  48.001

If it is rounded and dumped into a csv file

In [2]:
df.round({'price':2, 'change': 2}).to_csv('x/foo1.csv', index=False, lineterminator='\n')

The result does not align

$ cat ~/x/foo1.csv
symbol,price,change
A,8.22,6.6
B,7.01,7.24
C,3.97,-9.34
D,9.8,48.0

and can't easily be aligned using other command line tools

$ cat ~/x/foo1.csv | column -t -s, -R 2,3
symbol  price  change
A        8.22     6.6
B        7.01    7.24
C        3.97   -9.34
D         9.8    48.0

However, if format expression is used

In [3]:
formats = {'price': '{:.2f}', 'change': '{:.2f}'}
df2 = df.copy()
for col, f in formats.items():
    df2[col] = df2[col].apply(lambda x: f.format(x))
df2.to_csv('x/foo2.csv', index=False, lineterminator='\n')

the result still does not align

$ cat ~/x/foo2.csv
symbol,price,change
A,8.22,6.60
B,7.01,7.24
C,3.97,-9.34
D,9.80,48.00

but can be using command line tools

$ cat ~/x/foo2.csv | column -t -s, -R 2,3
symbol  price  change
A        8.22    6.60
B        7.01    7.24
C        3.97   -9.34
D        9.80   48.00

Ref:- https://stackoverflow.com/questions/20003290/output-different-precision-by-column-with-pandas-dataframe-to-csv - shows how to format different columns with different precision.

tags | round vs. format, float_format by column

align hundredths column with spaces

Use

import pandas as pd
from tabulate import tabulate

def to_fwf(df, fname):
    content = tabulate(df.values.tolist(), list(df.columns), tablefmt="plain")
    with open(fname, "w") as FileObj:
        FileObj.write(content)

pd.DataFrame.to_fwf = to_fwf

For example, consider

$ ipython
Python 3.10.9 | packaged by conda-forge | (main, Jan 11 2023, 15:15:40) [MSC v.1916 64 bit (AMD64)]
Type 'copyright', 'credits' or 'license' for more information
IPython 8.8.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]:
import pandas as pd
df = pd.DataFrame({
  'symbol': ['A', 'B', 'C', 'D'],
  'price': [8.222, 7.007, 3.971, 9.801],
  'change': [6.601, 7.241, -9.341, 48.001]})
df
Out[1]:
  symbol  price  change
0      A  8.222   6.601
1      B  7.007   7.241
2      C  3.971  -9.341
3      D  9.801  48.001

In [2]:
import pandas as pd
from tabulate import tabulate

def to_fwf(df, fname):
    content = tabulate(df.values.tolist(), list(df.columns), tablefmt="plain")
    with open(fname, "w") as FileObj:
        FileObj.write(content)

pd.DataFrame.to_fwf = to_fwf

round the data and dump it

In [3]:
df.round({'price':2, 'change': 2}).to_fwf('x/foo3.txt')

the result is aligned and space separated

$ cat ~/x/foo3.txt
symbol      price    change
A            8.22      6.6
B            7.01      7.24
C            3.97     -9.34
D            9.8      48

You can also do it using format expression

In [4]:
formats = {'price': '{:.2f}', 'change': '{:.2f}'}
df2 = df.copy()
for col, f in formats.items():
    df2[col] = df2[col].apply(lambda x: f.format(x))
df2.to_fwf('x/foo4.txt')

which gives the same result

$ cat ~/x/foo4.txt
symbol      price    change
A            8.22      6.6
B            7.01      7.24
C            3.97     -9.34
D            9.8      48

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