ProgPro1

This is a prosject to plot and visualize localized weather data and practice statistical analysis. It uses the Frost API provided by MET Norway and allows us to access MET Norway's historical archive of weather data from many different years

Basic Usage

Insert your client ID you can request from here into config_ex.ini and rename the file to config.ini

Functions in this project

All the functions in this are located in the Utils.py file so to use it start with import Utils

getdata()

Retreives data in the specified time frame from the Frost API, requires API key to be located in config.ini

The getData() function requires a date-range in the format: reftime="yyyy-mm-dd/yyyy-mm-dd" and how many lines you want to retrieve in the format n_lines=1. It returns a dataframe containing a relevant data. getData() is located in the ApiAndDataHandeling class

Example use:

df = Utils.ApiAndDataHandeling.getData(reftime="2020-04-01/2020-04-14", n_lines=1)

To change what elements are retrieved or the sources of the data, change it in the config.ini file

fixTable()

Turns long data into wide data and removes unnecessary colums to be easier to process in seaborn, pyplot and matplotlib

To use the fixTable() function specify a dataframe to "fix" and it returns a formatted version of the dataframe. The fixTable() function is in the ApiAndDataHandeling class

Example use:

df = Utils.ApiAndDataHandeling.fixTable(df)

fit_sin()

Fit sin to the input data, and return fitting parameters "amp", "omega", "phase", "offset", "freq", "period" and "fitfunc"

Requires two Pandas Series, one to represent each axis.

Example use:

res = Utils.regression.fit_sin(df.index, df["mean(air_temperature P1D)"])
sns.lineplot(x=df.index,  y=res["fitfunc"](df.index))

make_markdown_table()

Turns a Pandas array into a markdown table to be easier to read and present

Input: Python list with rows of table as lists
First element as list of headers.
Output: String to copy into a .md file

Example code:

liste = [["Data","Gjennomsnitt","Median", "Standaravikk"]]
for i in range(len(elements)):
    if i == 8: break
    a = []
    a.append(elements[i])
    a.append(str(mean[i]))
    a.append(str(median[i]))
    a.append(str(std[i]))
    liste.append(a)
print(utils.markdown.make_markdown_table(liste))