Description
Code Sample, a copy-pastable example if possible
from numpy import NaN
row = [2015, 1, 7.0, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, 0.4, NaN, NaN, NaN]
print([type(i) for i in row])
columns = ['year', 'month', 'day', '平均風速', '最大風速', '最大風向', '最大風速時間', '最大瞬間風速',
'最大瞬間風向','最大瞬間時間', '最多風向', '日照時間', '降雪', '最深積雪値', '最深積雪時間']
# Sorry some of the columns are in Japanese, but I believe it doesn't matter.
row_df = pd.DataFrame(columns=columns)
row_df.loc[0] = row
print(row_df.dtypes)My problem is, after running
row_df.loc[0] = row,the datatypes change
Output of pd.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.7.3.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 142 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.23.4
pytest: 3.8.0
pip: 19.1.1
setuptools: 41.0.1
Cython: 0.28.5
numpy: 1.15.4
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.5.0
sphinx: 1.7.9
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.8
feather: None
matplotlib: 2.2.3
openpyxl: 2.5.6
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.1.0
lxml: 4.2.5
bs4: 4.6.3
html5lib: 1.0.1
sqlalchemy: 1.2.11
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None