04 - Work Process

Professional Work Process

But first, let's get the work process straight.

We'll manage data using baserow.io (get an account or run your own instance), and create an API token.

So, let's say we have a view for data, like this:

Use the baserow-client library to read it:

In [1]:
from fxy.io.baserow import BaserowIO
API = 'https://data.mindey.com/'
API_TOKEN = 'C9gZFb15B8KAvWGihyr8YOGm62SSDlTD'
io = BaserowIO(API, token=API_TOKEN)
df = io.get_table(232)
df
1it [00:00,  4.64it/s]

Out[1]:
   id                   order uid                  date       Variable    Unit    value
0   1  1.00000000000000000000   1  2022-04-04T11:00:00Z  blood:glucose  mmol/l  5.34000
1   2  2.00000000000000000000   2  2022-05-20T12:00:00Z  blood:glucose  mmol/l  4.74000
2   3  3.00000000000000000000   3  2022-04-04T11:00:00Z  urine:glucose  mmol/l  4.12000
3   4  4.00000000000000000000   4  2022-05-20T12:00:00Z  urine:glucose  mmol/l  4.11000

Now, we can do the same mean computation, like:

In [2]: df.value = pandas.to_numeric(df.value)
        df.value.mean()
Out[2]: 4.5775

Tip: To apply "to_numeric" wherever possible, use something like:

df_numeric = df.apply(pandas.to_numeric, errors='coerce').fillna(df)

Read more about type conversions here.