It would help if you show how df
is defined. What does df.info()
report? This will show us the dtypes of the columns.
There are many ways that dates can be represented: as strings, ints, floats, datetime.datetime, NumPy datetime64s, Pandas Timestamps, or Pandas DatetimeIndex. The correct way to plot it depends on what you have.
Here is an example showing your code works if df.index
is a DatetimeIndex:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import stats
index = pd.date_range(start='2000-1-1', end='2015-1-1', freq='M')
N = len(index)
poisson = (stats.poisson.rvs(1000, size=(N,3))/100.0)
poisson.sort(axis=1)
df = pd.DataFrame(poisson, columns=['lwr', 'Rt', 'upr'], index=index)
plt.fill_between(df.index, df.lwr, df.upr, facecolor='blue', alpha=.2)
plt.plot(df.index, df.Rt, '.')
plt.show()
If the index has string representations of dates, then (with Matplotlib version 1.4.2) you would get a TypeError:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import stats
index = pd.date_range(start='2000-1-1', end='2015-1-1', freq='M')
N = len(index)
poisson = (stats.poisson.rvs(1000, size=(N,3))/100.0)
poisson.sort(axis=1)
df = pd.DataFrame(poisson, columns=['lwr', 'Rt', 'upr'])
index = [item.strftime('%Y-%m-%d') for item in index]
plt.fill_between(index, df.lwr, df.upr, facecolor='blue', alpha=.2)
plt.plot(index, df.Rt, '.')
plt.show()
yields
File "/home/unutbu/.virtualenvs/dev/local/lib/python2.7/site-packages/numpy/ma/core.py", line 2237, in masked_invalid
condition = ~(np.isfinite(a))
TypeError: Not implemented for this type
In this case, the fix is to convert the strings to Timestamps:
index = pd.to_datetime(index)