Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Showing content from https://github.com/pandas-dev/pandas/issues/39336 below:

float formatters ignore nullable floating extension type · Issue #39336 · pandas-dev/pandas · GitHub

Pandas float formatters ignore the nullable floating extension types Float64 which was introduced with 1.2.0.
In particular, this is extremely confusing when using DataFrame.convert_dtypes since the default is now with convert_floating=True which converts all float colums to Float64 columns.

That is, the following does not produce the expected float formatting:

import pandas as pd
df = pd.DataFrame([0.123456789, 1.123456789, 2.123456789], columns=["value"])
df = df.convert_dtypes()
print(df.to_string(formatters=["{:.2f}".format]))

gives

      value
0  0.123457
1  1.123457
2  2.123457

I am not sure, whether this classifies as a bug or missing documentation (or both) however having not heard of this new nullable floating type Float64 I did not notice this subtle difference at first. Also, I did not expect DataFrame.convert_dtypes() to result in a non-formatable DataFrame. So, if Float64 is not expected to format as float64, the documentation should make this clear.
However, I believe the best would be that Float64 formats just as the regular float dtype.

The formatting should be applied to the Float64 dtype just as when using the float dtype such as

import pandas as pd
df = pd.DataFrame([0.123456789, 1.123456789, 2.123456789], columns=["value"])
print(df.to_string(formatters=["{:.2f}".format]))

which gives

  value
0  0.12
1  1.12
2  2.12

INSTALLED VERSIONS
------------------
commit           : 3e89b4c4b1580aa890023fc550774e63d499da25
python           : 3.8.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.10.9-arch1-1
Version          : #1 SMP PREEMPT Tue, 19 Jan 2021 22:06:06 +0000
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : None
LANG             : en_DK.UTF-8
LOCALE           : en_DK.UTF-8
pandas           : 1.2.0
numpy            : 1.19.2
pytz             : 2020.5
dateutil         : 2.8.1
pip              : 20.3.3
setuptools       : 51.0.0.post20201207
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.2
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.2
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4