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my dataframe below:
<class 'pandas.core.frame.DataFrame'> Int64Index: 18922 entries, 7 to 77733 Data columns (total 4 columns): user_id 18922 non-null int64 event_id 18922 non-null int64 context 18922 non-null object created_at 18922 non-null datetime64[ns] dtypes: datetime64[ns](1), int64(2), object(1) memory usage: 739.1+ KB
I wrote a function to transform df['context'] to a dict like:
def json_parse(json_str): """ :param user_id: :param str: :return: """ try: juxinli_report = json.loads(json_str) except Exception as e: print(e) juxinli_report = dict() if juxinli_report: info = {} data = juxinli_report.get('data', {}) for key_1 in data.get('user_gray', {}): info[key_1] = data.get('user_gray', {}).get(key_1) return info
when I did:
jxl_report[:4].apply(lambda row: json_parse(row['context']), axis=1)
the result was strange, it should be a Series.
user_id event_id context created_at 7 NaN NaN NaN NaN 12 NaN NaN NaN NaN 15 NaN NaN NaN NaN 17 NaN NaN NaN NaN
but if I drop the column created_at or change its type to object, the result is expected, a Series.
created_at
jxl_report = jxl_report.drop(['created_at'], axis=1) # or # jxl_report['created_at'] = jxl_report['created_at'].astype('str')
7 {'contacts_class1_blacklist_cnt': 2, 'user_pho... 12 {'contacts_class1_blacklist_cnt': 0, 'user_pho... 15 {'contacts_class1_blacklist_cnt': 0, 'user_pho... 17 {'contacts_class1_blacklist_cnt': 0, 'user_pho...
pd.show_versions()
commit: None python: 3.6.1.final.0 python-bits: 64 OS: Windows OS-release: 10 machine: AMD64 processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel byteorder: little LC_ALL: None LANG: None LOCALE: None.None
pandas: 0.20.3 pytest: None pip: 9.0.1 setuptools: 28.8.0 Cython: None numpy: 1.13.3 scipy: 0.19.1 xarray: None IPython: 6.1.0 sphinx: 1.6.3 patsy: 0.4.1 dateutil: 2.6.1 pytz: 2017.2 blosc: None bottleneck: None tables: None numexpr: None feather: None matplotlib: 2.0.2 openpyxl: None xlrd: 1.1.0 xlwt: None xlsxwriter: None lxml: None bs4: 4.6.0 html5lib: 0.9999999 sqlalchemy: 1.1.9 pymysql: 0.7.11.None psycopg2: None jinja2: 2.9.6 s3fs: None pandas_gbq: None pandas_datareader: None
The text was updated successfully, but these errors were encountered:
you need a self-contained copy-pastable example that repros, its possible you are seeing #15628
Sorry, something went wrong.
Let us know if you can provide a reproducible example http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
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my dataframe below:
I wrote a function to transform df['context'] to a dict like:
when I did:
the result was strange, it should be a Series.
but if I drop the column
created_at
or change its type to object, the result is expected, a Series.Output of
pd.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.20.3
pytest: None
pip: 9.0.1
setuptools: 28.8.0
Cython: None
numpy: 1.13.3
scipy: 0.19.1
xarray: None
IPython: 6.1.0
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: 1.1.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.6.0
html5lib: 0.9999999
sqlalchemy: 1.1.9
pymysql: 0.7.11.None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
The text was updated successfully, but these errors were encountered: