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Description
Series.replace() should potentially raise an exception if an invalid argument is given? I am new to pandas and this is more of a question. This is a user error on my part, but possible improvement to replace.
df = pd.DataFrame(
{
'one': ['1','1 ','10'],
'two': ['1 ', '20 ', '30 ']
})
# creates
one two
0 1 1
1 1 20
2 10 30
# I intentionally added a space in df.one. So df.one.value_counts() results in
1 1
10 1
1 1
# I want to strip the spaces around all values in df.one
# so that value_counts() only has 1 and 10 with values 2 and 1 respectively.
# The following does not work.
df.one.replace(lambda x: x.strip(), inplace=True)
Problem description
Series.replace() accepts "str, regex, list, dict, Series, numeric, or None"
. So I understand why the above does not work. But as @toobaz pointed out on gitter, when a lambda is passed, replace should probably raise an error?
Expected Output
Raises TypeError
Output of pd.show_versions()
[paste the output of pd.show_versions()
here below this line]
INSTALLED VERSIONS
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
pandas: 0.20.3
pytest: None
pip: 9.0.1
setuptools: 36.3.0
Cython: None
numpy: 1.13.1
scipy: 0.19.1
xarray: None
IPython: 6.1.0
sphinx: 1.6.3
patsy: None
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.8
xlrd: 1.0.0
xlwt: None
xlsxwriter: None
lxml: 3.8.0
bs4: None
html5lib: 0.999999999
sqlalchemy: 1.1.14
pymysql: 0.7.11.None
psycopg2: None
jinja2: 2.8.1
s3fs: None
pandas_gbq: None
pandas_datareader: None