Plotting simple time series using pandas

Question

I'm trying to plot a simple time series chart, seeing how closing prices have changed day over day. This is my code:

from yahoo_finance import Share
from datetime import datetime
import pandas as pd
import matplotlib.pyplot as plt

yahoo = Share('YHOO')

stock = yahoo

start_date = '2015-12-01'
end_date = '2015-12-10'

historical_table = pd.DataFrame(stock.get_historical(start_date, end_date))
historical_table = historical_table[['Date','Symbol','Close','High','Low','Open']]

def convert_dates(date):
    date = datetime.strptime(date, "%Y-%m-%d")
    return date

historical_table['Date'].apply(convert_dates)

print historical_table['Date']

x = historical_table['Date']
y = historical_table['Close']

plt.plot(x,y)
plt.show()

This is the error message that I get:

Traceback (most recent call last):
  File "finance.py", line 45, in <module>
    plt.plot(x,y)
  File "/Users/paulzovighian/anaconda/lib/python2.7/site-packages/matplotlib/pyplot.py", line 3099, in plot
    ret = ax.plot(*args, **kwargs)
  File "/Users/paulzovighian/anaconda/lib/python2.7/site-packages/matplotlib/axes/_axes.py", line 1373, in plot
    for line in self._get_lines(*args, **kwargs):
  File "/Users/paulzovighian/anaconda/lib/python2.7/site-packages/matplotlib/axes/_base.py", line 304, in _grab_next_args
    for seg in self._plot_args(remaining, kwargs):
  File "/Users/paulzovighian/anaconda/lib/python2.7/site-packages/matplotlib/axes/_base.py", line 263, in _plot_args
    linestyle, marker, color = _process_plot_format(tup[-1])
  File "/Users/paulzovighian/anaconda/lib/python2.7/site-packages/matplotlib/axes/_base.py", line 85, in _process_plot_format
    if fmt.find('--') >= 0:
  File "/Users/paulzovighian/anaconda/lib/python2.7/site-packages/pandas/core/generic.py", line 2246, in __getattr__
    (type(self).__name__, name))
AttributeError: 'Series' object has no attribute 'find'

When looking online, I tend to see examples of 'hardcoded' variables, but I don't get how to apply this to a dataframe column - I found that I should use strptime to identify what format my date column is, but I don't know if this has any effect (I get the same error if I comment out the convert_dates apply method).

Thanks in advance for any help here, and open to any suggestions to streamlining this approach.

Bart · Accepted Answer · 2015-12-15 01:11:11Z

2

Seems like a format problem, try this:

# %matplotlib inline # Use this if you are using Jupyter notebook and want plots inline
from yahoo_finance import Share
from datetime import datetime
import pandas as pd
import matplotlib.pyplot as plt

yahoo = Share('YHOO')

stock = yahoo

start_date = '2015-12-01'
end_date = '2015-12-10'

historical_table = pd.DataFrame(stock.get_historical(start_date, end_date))
historical_table = historical_table[['Date','Symbol','Close','High','Low','Open']]

historical_table['Date'] = pd.to_datetime(historical_table['Date']) #date to datetime format
historical_table['Close']  = [float(x) for x in historical_table['Close']] #close price to floats

x = historical_table['Date']
y = historical_table['Close']

plt.plot(x,y)
plt.show()

edited Dec 15, 2015 at 1:11

Bart

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answered Dec 14, 2015 at 23:46

Ezer K

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1 Comment

ploo Over a year ago

Thank you! Go figure, of course pandas has a built in method to convert to datetime haha

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