this is driving me nuts, I can't plot column 'b' it plots only column 'A'.....
this is my code, no idea what I'm doing wrong, probably something silly... the dataframe seems ok, weirdness also is that I can access both df['A'] and df['b'] but only df['A'].plot() works, if I issue a df['b'].plot() I get this error :
Traceback (most recent call last): File "C:\Python27\lib\site-packages\IPython\core\interactiveshell.py", line 2883, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "", line 1, in df['b'].plot() File "C:\Python27\lib\site-packages\pandas\tools\plotting.py", line 2511, in plot_series **kwds) File "C:\Python27\lib\site-packages\pandas\tools\plotting.py", line 2317, in _plot plot_obj.generate() File "C:\Python27\lib\site-packages\pandas\tools\plotting.py", line 921, in generate self._compute_plot_data() File "C:\Python27\lib\site-packages\pandas\tools\plotting.py", line 997, in _compute_plot_data 'plot'.format(numeric_data.class.name)) TypeError: Empty 'Series': no numeric data to plot
import sqlalchemy
import pandas as pd
import matplotlib.pyplot as plt
engine = sqlalchemy.create_engine(
'sqlite:///C:/Users/toto/PycharmProjects/my_db.sqlite')
tables = engine.table_names()
dic = {}
for t in tables:
sql = 'SELECT t."weight" FROM "' + t + '" t WHERE t."udl"="IBE SM"'
dic[t] = (pd.read_sql(sql, engine)['weight'][0], pd.read_sql(sql, engine)['weight'][1])
df = pd.DataFrame.from_dict(dic, orient='index').sort_index()
df = df.set_index(pd.DatetimeIndex(df.index))
df.columns = ['A', 'b']
print(df)
print(df.info())
df.plot()
plt.show()
this is the 2 print
A b
2014-08-05 1.81 3.39
2014-08-06 1.81 3.39
2014-08-07 1.81 3.39
2014-08-08 1.80 3.37
2014-08-11 1.79 3.35
2014-08-13 1.80 3.36
2014-08-14 1.80 3.35
2014-08-18 1.80 3.35
2014-08-19 1.79 3.34
2014-08-20 1.80 3.35
2014-08-27 1.79 3.35
2014-08-28 1.80 3.35
2014-08-29 1.79 3.35
2014-09-01 1.79 3.35
2014-09-02 1.79 3.35
2014-09-03 1.79 3.36
2014-09-04 1.79 3.37
2014-09-05 1.80 3.38
2014-09-08 1.79 3.36
2014-09-09 1.79 3.35
2014-09-10 1.78 3.35
2014-09-11 1.78 3.34
2014-09-12 1.78 3.34
2014-09-15 1.78 3.35
2014-09-16 1.78 3.35
2014-09-17 1.78 3.35
2014-09-18 1.78 3.34
2014-09-19 1.79 3.35
2014-09-22 1.79 3.36
2014-09-23 1.80 3.37
... ... ...
2014-12-10 1.73 3.29
2014-12-11 1.74 3.27
2014-12-12 1.74 3.25
2014-12-15 1.74 3.24
2014-12-16 1.74 3.27
2014-12-17 1.75 3.28
2014-12-18 1.76 3.29
2014-12-19 1.04 1.39
2014-12-22 1.04 1.39
2014-12-23 1.04 1.4
2014-12-24 1.04 1.39
2014-12-29 1.04 1.39
2014-12-30 1.04 1.4
2015-01-02 1.04 1.4
2015-01-05 1.04 1.4
2015-01-06 1.04 1.4
2015-01-07 NaN 1.39
2015-01-08 NaN 1.39
2015-01-09 NaN 1.39
2015-01-12 NaN 1.38
2015-01-13 NaN 1.38
2015-01-14 NaN 1.38
2015-01-15 NaN 1.38
2015-01-16 NaN 1.38
2015-01-19 NaN 1.39
2015-01-20 NaN 1.38
2015-01-21 NaN 1.39
2015-01-22 NaN 1.4
2015-01-23 NaN 1,4
2015-01-26 NaN 1.41
[107 rows x 2 columns]
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 107 entries, 2014-08-05 00:00:00 to 2015-01-26 00:00:00
Data columns (total 2 columns):
A 93 non-null float64
b 107 non-null object
dtypes: float64(1), object(1)
memory usage: 2.1+ KB
None
Process finished with exit code 0
