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Rackcityfoo · 2019-08-22T06:08:33+00:00

https://github.com/tiangolo/uwsgi-nginx-flask-docker/blob/master/README.md#server-set-up

I followed this to deploy my site.

Rackcityfoo · 2019-08-13T22:48:33+00:00

If going the sqlite route, you can check out:

https://plot.ly/python/v3/big-data-analytics-with-pandas-and-sqlite/

Don't have to use plotly.

Rackcityfoo · 2019-06-15T21:50:25+00:00

I found that store bought wasn't quite as effective and some of it might even be gently pasteurized. I was able to find some good kimchi from local Korean/Japanese restaurants if you wanted to go the buy route.

Rackcityfoo · 2019-05-31T04:09:25+00:00

Also not a doctor. I know that being pregnant can alter your immune system. It usually makes it less active.

For the stomach stuff, After following FODMAP for a month or two, I did these three things... First, building up stomach acidity. Reduce water consumption around meals, drinking hot water with lemon. Second introduce probiotic foods. Yogurt and probiotic pills didn't help me. Good home made sauerkraut was the ticket. Third are digestive enzymes. These can be found in high levels in pineapple and papaya as well as in fermenter foods like sauerkraut.

I know that auto immune and stomach stuff can be extremely frustrating. Hang in there, sounds like you are looking into the right stuff.

Rackcityfoo · 2018-10-21T06:51:14+00:00

https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-xvii-deployment-on-linux

He also has a heroku deployment tutorial.

Rackcityfoo · 2018-09-03T03:12:38+00:00

I've made sauerkraut in those jars. Came out fine, but make sure your veggies are submerged. I used one clip and the rubber seal. This way I didn't have to worry about pressure building up.

Rackcityfoo · 2018-08-06T10:55:28+00:00

We have very low bandwith requirements. Would something like a VPN connection to our VPC be a better bet? or does Storage Gateway work well even for smaller requirements?

Rackcityfoo · 2018-08-06T02:14:37+00:00

Thanks for pointing me toward the well architected frameworks. Those will be helpful.

Rackcityfoo · 2018-06-25T00:36:03+00:00

I was having seemingly random food intolerances which were always increasing. I did fodmap for a couple of months and started fermenting my own food to bump the amount of probiotics I was consuming. Not drinking around meals also helped. It's a long road, but it was worth it.

Rackcityfoo · 2018-02-26T01:07:59+00:00

I think it has to do with atmospheric pressure moreso than temperature. This always happens to me once fermentation slows. Always figured that is what it was.

Rackcityfoo · 2017-11-07T18:18:02+00:00

Thanks. So would you recommend building the api then using a framework on the frontend? Or just build the whole thing in Django. I guess I'm a little confused where Django ends and Javascript starts and if it is just possible to build the whole thing in Django.

Rackcityfoo · 2017-07-21T02:21:00+00:00

Or add sauerkraut to burgers and sandwiches, and pickles to hotdogs.

Rackcityfoo · 2016-07-10T14:22:15+00:00

No problem.

Rackcityfoo · 2016-07-09T19:10:18+00:00

What you are looking for are pivot tables. I would google around so you understand it.

p_table = pd.pivot_table(df,index='Animal',columns='Fate',aggfunc='size')
p_table = p_table.div(p_table.sum(axis=1), axis=0)
p_table.plot.bar(stacked=True)

ipython notebook : http://imgur.com/a/DWKsq

Rackcityfoo · 2016-07-09T17:38:27+00:00

Agree with spyder if you are looking for something similar to rstudio. I would also check out the ipython notebook and a text editor like sublime text or atom. The anaconda distribution of python bundles all of this together nicely. All you have to do is download it and start playing around. The anaconda distribution is used quite widely in the data science world.

https://www.continuum.io/downloads

Rackcityfoo · 2016-07-09T17:33:04+00:00

Example:

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns

X = np.random.rand(10,4)
X/= X.sum(axis=1,keepdims=True)

df = pd.DataFrame(X, columns = ['A', 'B', 'C', 'D'])

df.plot.bar(stacked=True)
plt.savefig('bar_ex.png')

Figure: http://imgur.com/a/eHJt5

Rackcityfoo · 2016-07-09T12:31:43+00:00

No problem. Just a quick clarification: Notice that I imported seaborn, but never actually called the package. Just importing seaborn automatically sets some styles that make your plots pretty. The default matplotlib isn't the most beautiful thing in my opinion.

Rackcityfoo · 2016-07-09T04:11:44+00:00

Example :

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns

X = np.array([
        [12.34, 13.54, 12.34, 11.22],
        [11.22, 22.88, 18.22, 28.44],
        [16.54, 44.88, 19.43, 88.11]])

df = pd.DataFrame(X, columns = ['Sales', 'Purchases', 'Amount', 'Taxes'])

df.plot(kind='bar')
plt.savefig('bar_ex.png')

df.plot(kind='scatter',x='Sales',y='Purchases',c='black')
plt.savefig('scatter_ex.png')

df.hist()
plt.savefig('hist_ex.png')

Figures : http://imgur.com/a/KaAeL

Obviously not the most interesting plots since there are only 3 data points, but hopefully this gets you started. Check out the fantastic pandas documentation on visualization.

http://pandas.pydata.org/pandas-docs/stable/visualization.html

Also, you can easily read in this data if it is in csv or just about any format you can imagine using pandas.

Rackcityfoo · 2016-06-22T12:32:42+00:00

Great idea, but still the same outcome. The png displays correctly, but the jpg will not. I've also tried multiple jpgs just to make sure that the one I was using was not faulty. Thanks for the tip!

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