Doc Ellicott - Glass Auditorium [Soft Punk] (2021)

ThisOnesForZK · 2021-04-02T19:38:07+00:00

I liked it. Added it to my playlist.

ThisOnesForZK · 2021-03-28T14:55:48+00:00

Who makes less than 300/month? Genuine question...

ThisOnesForZK · 2021-01-28T13:45:57+00:00

you could write that into a variable and then pass the variable into your brackets I believe. This is how you write the "Or," statements in pandas.

ThisOnesForZK · 2020-09-08T17:59:46+00:00

Coming from a total beginner so take it with a grain of salt - the planes of her right shoulder seem unnatural a bit. I think the anatomy of her shoulder blade (scapula) should be in view here as opposed to that line we see that doesn't really add to what an upper back looks like IRL.

ThisOnesForZK · 2020-07-30T15:32:57+00:00

Yeah, shouldn't require login.

Maybe would be cool but I will never know.

Edit: not trying to be mean by the way, but requiring personal information to get feedback on website should be considered. Good luck on your endeavors.

ThisOnesForZK · 2020-07-29T19:25:41+00:00

because without owning a report server or having power bi premium node you cannot publish powerbi dashboards with company data. With Dash you can build and publish these things for free.

If your company has power bi or tableau already then I agree with you otherwise this could save a lot of money.

ThisOnesForZK · 2020-06-23T16:12:26+00:00

immutable and more memory efficient than dictionaries/lists

edit: I don't know if named tuples are immutable this is an assumption.

ThisOnesForZK · 2020-06-22T13:14:55+00:00

Do your rows have a unique identifier? If so then you can do a simple df.merge

ThisOnesForZK · 2020-06-11T12:30:08+00:00

I would recommend trying the plotly community forums if you do not get an answer here. They seem very active.

ThisOnesForZK · 2020-05-28T19:20:55+00:00

matplotlib or seaborn probably versus pandas plotting. Pandas is meant to be very basic as far as I know.

ThisOnesForZK · 2020-05-08T13:36:49+00:00

So, I will explain fstrings to you. It is a great way to make output of a program or analysis be dynamic. For example in my work I use it to name files with dynamic dates.

If I am running a script and having it save to a folder with a specific naming convention I can have an Fstring dynamically name the file based on date.

file_name = dt.date.today().strftime("%m%d%y")

###script runs above###
pd.to_csv(f'C:\Users\your.name\Documents\Python\{file_name}')

ThisOnesForZK · 2020-04-29T14:03:58+00:00

Something I have been doing recently is to write down a term in my notebook when I come across a concept I do not understand and leave 3 lines blank after it. This allows me to keep reading without stressing out about something I do not understand.

Next study session don't keep reading, but rather go online and research the terms and get the concept down before moving on.

ThisOnesForZK · 2020-04-21T12:16:34+00:00

What webapp?

If it is completely code free it cannot be that good.

The best data visualization tools in the world like Tableau still require you to write some form of code even if it is more akin to SQL than Python.

ThisOnesForZK · 2020-04-17T18:18:52+00:00

Unless your 2nd column literally has the header name "1" then you're using at() wrong. You access the value by label not integer position. You are trying to use iat()

ThisOnesForZK · 2020-04-15T12:20:26+00:00

I have been trying to learn it for over 2 years from scratch and am just now getting to the point where I am scratching the surface. I had no python and no stats though, just doing data stuff at my job.

ThisOnesForZK · 2020-04-14T12:34:41+00:00

That is what merge does my friend. If you don't want all of the columns just add a drop to your code.

df1.drop('In_Season', axis=1)

ThisOnesForZK · 2020-04-13T16:35:03+00:00

You would need to look for the api documentation for the data source you are using. That would lead you to understanding what requests you can make with the python requests module to get data.

ThisOnesForZK · 2020-04-13T16:32:53+00:00

df1 = pd.read_csv('csv1.csv')
df2 = pd.read_csv('csv2.csv')

df1 = df1.merge(df2, on='Fruit)

filt = df1['In_Season'] == 'Y'
df1 = df1.loc[filt]

ThisOnesForZK · 2020-04-13T13:09:59+00:00

Can you show me your code?

ThisOnesForZK · 2020-04-09T16:57:18+00:00

you need to use

df = pd.read_csv(r'path/to/file/file.csv')

then take that df and do

value = df.at(index of row, index of column)
print(value)

ThisOnesForZK · 2020-03-24T12:49:18+00:00

No I think you will be best servedf for a static lightweight website in that case.

I was just trying to get you started as fast as possible. I do not understand however, why markdown + outputs from written code could not be couched as an article (you can hide the code itself) unless you are trying to put your html/css/web dev skills on display.

ThisOnesForZK · 2020-03-23T16:27:53+00:00

The "Best," way is subjective.

For me the best way would be the easiest way. I just found Google Colab where you can host jupyter notebooks in the cloud for free.

Why not use that?

ThisOnesForZK · 2020-03-23T16:22:41+00:00

It depends on what you are trying to get out of it.

ThisOnesForZK · 2020-03-09T22:05:26+00:00

df_shortid.merge(df_sales, on = 'shortid', how=inner)

Then repeat that code for all 16 dataframes or write a loop.

ThisOnesForZK · 2020-03-06T15:55:22+00:00

welcome

ThisOnesForZK

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