Series constructor skips dtype=str conversion for list data

[kbg]

Code Example

from pandas import Series, DataFrame

int_list = [1, 2, 3]

s1 = Series(int_list)
s2 = Series(int_list, dtype=float)
s3 = Series(int_list, dtype=str)
s4 = Series(int_list, dtype='U')
s5 = Series(Series(int_list), dtype=str)

print('Series element type:')
print('  s1:', type(s1[0]))
print('  s2:', type(s2[0]))
print('  s3:', type(s3[0]))
print('  s4:', type(s4[0]))
print('  s5:', type(s5[0]))

f1 = DataFrame(int_list)
f2 = DataFrame(int_list, dtype=float)
f3 = DataFrame(int_list, dtype=str)
f4 = DataFrame(int_list, dtype='U')
f5 = DataFrame(DataFrame(int_list), dtype=str)

print('\nDataFrame element type:')
print('  f1:', type(f1.iloc[0, 0]))
print('  f2:', type(f2.iloc[0, 0]))
print('  f3:', type(f3.iloc[0, 0]))
print('  f4:', type(f4.iloc[0, 0]))
print('  f5:', type(f5.iloc[0, 0]))

Output:

Series element type:
  s1: <class 'numpy.int64'>
  s2: <class 'numpy.float64'>
  s3: <class 'int'>
  s4: <class 'int'>
  s5: <class 'str'>

DataFrame element type:
  f1: <class 'numpy.int64'>
  f2: <class 'numpy.float64'>
  f3: <class 'str'>
  f4: <class 'str'>
  f5: <class 'str'>

Problem description

When creating a Series from a list using dtype=str, the data elements are not converted to strings. The Series instance apparently just keeps the original (Python) data type in this case.

This problem does not occur when, instead of a list, another Series is used as input data (s5 in the example above). It also does not happen when creating DataFrame instances from list data.

Expected Output

Series element type:
  s1: <class 'numpy.int64'>
  s2: <class 'numpy.float64'>
  s3: <class 'str'>
  s4: <class 'str'>
  s5: <class 'str'>

DataFrame element type:
  f1: <class 'numpy.int64'>
  f2: <class 'numpy.float64'>
  f3: <class 'str'>
  f4: <class 'str'>
  f5: <class 'str'>

Output of pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Linux
OS-release: 4.11.3-1-ARCH
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.20.1
pytest: 3.1.1
pip: 9.0.1
setuptools: 36.0.1
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 5.3.0
sphinx: 1.6.1
patsy: None
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999999999
sqlalchemy: 1.1.10
pymysql: None
psycopg2: 2.7.1 (dt dec pq3 ext lo64)
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: 0.4.0

[jreback]

hmm, the array-like should be converted exactly like .astype(str), IOW

Series(arr, dtype=str) should be equal to Series(arr).astype(str).

I think str is treated as object here. pull-requests welcome.

[kbg]

I don't have the time to fix it right now. Maybe I'll find some time at the weekend.

In case somebody else wants to fix this: The problem is located at the very end of pandas.core.series._sanitize_array() which is called by the Series constructor.

There is also an issue with scalar input values:

>>> type(pandas.Series(1.0, dtype=str)[0])
float

which needs some additional changes near the end of pandas.core.series._sanitize_array().