Do this: In [43]: temp2.str[-1] Out[43]: 0 p500 1 p600 2 p700 Name: ticker So all together it would be: >>> temp = pd.DataFrame({‘ticker’ : [‘spx 5/25/2001 p500’, ‘spx 5/25/2001 p600’, ‘spx 5/25/2001 p700’]}) >>> temp[‘ticker’].str.split(‘ ‘).str[-1] 0 p500 1 p600 2 p700 Name: ticker, dtype: object
Not the most efficient, but straight forward and concise: if len(x) > len(set(x)): pass # do something Probably won’t make much of a difference for short lists.
The short version is: The efficient way to use readlines() is to not use it. Ever. I read some doc notes on readlines(), where people has claimed that this readlines() reads whole file content into memory and hence generally consumes more memory compared to readline() or read(). The documentation for readlines() explicitly guarantees that it … Read more
pd.DataFrame.loc can take one or two indexers. For the rest of the post, I’ll represent the first indexer as i and the second indexer as j. If only one indexer is provided, it applies to the index of the dataframe and the missing indexer is assumed to represent all columns. So the following two examples … Read more
I already posted this in another thread but I think it fits better in this one: UPDATE (30.07.2014): I re-run the the benchmark on our new HPC. Both the hardware as well as the software stack changed from the setup in the original answer. I put the results in a google spreadsheet (contains also the … Read more
Here’s a great python module someone wrote to solve this problem after seeing this question: https://github.com/john-kurkowski/tldextract The module looks up TLDs in the Public Suffix List, mantained by Mozilla volunteers Quote: tldextract on the other hand knows what all gTLDs [Generic Top-Level Domains] and ccTLDs [Country Code Top-Level Domains] look like by looking up the … Read more
If you want the sum of all bars to be equal unity, weight each bin by the total number of values: weights = np.ones_like(myarray) / len(myarray) plt.hist(myarray, weights=weights) Hope that helps, although the thread is quite old… Note for Python 2.x: add casting to float() for one of the operators of the division as otherwise … Read more
You have two options: Use float.as_integer_ratio(): >>> (0.25).as_integer_ratio() (1, 4) (as of Python 3.6, you can do the same with a decimal.Decimal() object.) Use the fractions.Fraction() type: >>> from fractions import Fraction >>> Fraction(0.25) Fraction(1, 4) The latter has a very helpful str() conversion: >>> str(Fraction(0.25)) ‘1/4’ >>> print Fraction(0.25) 1/4 Because floating point values … Read more
EDIT Changed aspect=”normal to aspect=”auto’ since that changed in more recent versions of matplotlib (thanks to @Luke19). Assuming : import matplotlib.pyplot as plt To make a figure without the frame : fig = plt.figure(frameon=False) fig.set_size_inches(w,h) To make the content fill the whole figure ax = plt.Axes(fig, [0., 0., 1., 1.]) ax.set_axis_off() fig.add_axes(ax) Then draw your … Read more
You can also use tail with groupby to get the last n values of the group: df.sort_values(‘date’).groupby(‘id’).tail(1) id product date 2 220 6647 2014-10-16 8 901 4555 2014-11-01 5 826 3380 2015-05-19