python - ValueError: invalid literal for float(): when inserted substring from "2015-05-21T18:11:55" into dataframe -

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i have key value pair in json-derived dictionary looks this:

u'local_start_time': u'2015-05-21t18:11:55.000z'

when try insert portion of string dataframe error:

  file "fix_runs_prepare.py", line 63, in <module>     df.set_value(i, name, str(g[name])[0:19])   file "/usr/local/lib/python2.7/dist-packages/pandas/core/frame.py", line 1679, in set_value     engine.set_value(series.values, index, value)   file "pandas/index.pyx", line 118, in pandas.index.indexengine.set_value (pandas/index.c:3382)   file "pandas/index.pyx", line 132, in pandas.index.indexengine.set_value (pandas/index.c:3264)   file "pandas/src/util.pxd", line 60, in util.set_value_at (pandas/index.c:15472) valueerror: invalid literal float(): 2015-05-21t18:11:55

this when inserting using call:

run_info = df['run_info'] in range(len(df['run_info'])):     g = run_info[i]         name in name_list:         if g.get(name):             if name 'local_start_time':                 df.set_value(i, name, str(g[name])[0:19])             else:                 df.set_value(i, name, g[name])

i same error if don't first cast string:

                df.set_value(i, name, g[name][0:19])

on other hand if insert string literal "baloney" not error. think funky going on because string using begins number . that's why tried explicitly casting str() since didn't work i'm out of ideas. else should try?

**addendum here df.head()

                        _id country      id_2  location_fail  no_location  \ 0  55721992afe58716147ed3e8     nan    212508            nan            1 1  55721992afe58716147ed3e9     nan    212508            nan          nan 2  55721992afe58716147ed3ea     nan    212508            nan          nan 3  55721992afe58716147ed3ec     nan    400134              1            1 4  557219d4afe58716147edbd4  poland    513751            nan          nan           run                                           run_info  gender  \ 0  526956965  {u'tagged_users': [], u'hashtags': [], u'feed_...     nan 1  512136570  {u'tagged_users': [], u'hashtags': [], u'feed_...     nan 2  510056284  {u'distance': 0.0, u'playlist': [], u'author':...     nan 3  525398093  {u'motivation': {u'duration': 1.5, u'distance'...     nan 4  477634373  {u'tagged_users': [], u'hashtags': [], u'speed...     nan     weight  height  ...   descent  calories  heart_rate  heart_rate_max  steps  \ 0     nan     nan  ...       nan       nan         nan             nan    nan 1     nan     nan  ...       nan       nan         nan             nan    nan 2     nan     nan  ...       nan       nan         nan             nan    nan 3     nan     nan  ...       nan       nan         nan             nan    nan 4     nan     nan  ...       nan       nan         nan             nan    nan     notes  speed_avg  heart_rate_avg  speed_max  local_start_time 0    nan        nan             nan        nan   nan 1    nan        nan             nan        nan   nan 2    nan        nan             nan        nan   nan 3    nan        nan             nan        nan   nan 4    nan        nan             nan        nan   nan

the problem pandas.dataframe treats datatype of cells object , try infer datatype if don't specify explicitly.

to avoid that, explicitly set datatype of columns want to, using dataframe.astype:

df[[name]] = df[[name]].astype(str) # or df[[name]] = df[[name]].astype(float)

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