aecorn

import requests
import pandas as pd
import itertools


def get_table_ids(shortname: str) -> list[str]:
    shortname_content = requests.get("https://data.ssb.no/api/pxwebapi/v2-beta/navigation/{shortname}").json()
    return [x for x in [table.get("id") for table in shortname_content.get("folderContents")] if x.isdigit() and len(x) == 5]

def table_dataframe(tableid: str) -> pd.DataFrame:

aecorn

import { QuartzTransformerPlugin } from "../types"

const secret_regex = new RegExp(/(---secret[\s\S]*?secret---)/, "g")

export const SecretRemover: QuartzTransformerPlugin = () => {
    return {
      name: "SecretRemover",
      textTransform(_ctx, src) {
          src = src.toString()
          src = src.replaceAll(secret_regex, (value, ...capture) => {

aecorn

import pandas as pd
from pandas.io.sas.sas7bdat import SAS7BDATReader

def proc_contents(path: str) -> pd.DataFrame:
    sasfile = SAS7BDATReader(path,
                             convert_dates=False,
                             blank_missing=False,
                             convert_text=False,
                             chunksize=1,
                             )

aecorn

import pandas as pd

class Wrapper:
    def __init__(self, df: pd.DataFrame):
        self.data = df
    
    def __str__(self):
        return str(self.data.info())
    
    def __repr__(self):

aecorn

import json

labels_script = """
fnr = 'Fødselsnummer'
snr_nudb = 'Snr'
kjoenn = 'kjønn (lages ut fra snr)'
fodt_aar = 'fødselsår yyyy (lages ut fra snr)'
fodt_dato = 'fødselsdato yyyymmdd (hentes fra befolkningsfila)'
fodato = 'Oppholdsdato første opphold i Norge yyyymmdd (hentes fra befolkningsfila)'
fodeland = 'Fødeland (hentes fra befolkningsfila)'

aecorn

colors = [
"#1a9d49",
"#3396d2",
"#9582bb",
"#f26539",
"#d2bc2a",
"#6f9090"]

alpha = 0.65
# Convert colors to rgba, and give them the set opacity

aecorn

from copy import deepcopy
from collections import Counter
def restructure_belop(inp: dict) -> dict:
    skjemaer_ny = deepcopy(skjemaer)
    for skjema_gml, skjema_ny in zip(skjemaer, skjemaer_ny):
        counts = Counter([elem["funksjon/kapittel"] for elem in skjema_gml["regnskap"]])
        code_groups = [k for k, v in counts.items() if v > 1]
        for code in code_groups:
            elems = [x for x in skjema_gml["regnskap"] if x["funksjon/kapittel"] == code]
            for elem in elems:

aecorn

let
tableId = "NBA040",
PostContents = "{
  ""query"": [
    {
      ""code"": ""AgeGroup"",
      ""selection"": {
        ""filter"": ""item"",
        ""values"": [
          ""Y15-74""

aecorn

import matplotlib.pyplot as plt
import seaborn as sns

# Initialize seaborn object
d = sns.kdeplot(data = dataset, shade = True, shade_lowest = False, cmap = 'vlag')
# Set some attributes on the seaborn-object
d.set(ylim=(0,55), xlabel = 'Two first numbers of NACE', ylabel = 'Number of Employees per company')
# Display the visual
plt.show()

aecorn

import matplotlib.pyplot as plt
import seaborn as sns

# Limit data
dataset = dataset[dataset.NACE_first.isin([1, 2, 3])]
# Initialize seaborn object
v = sns.violinplot(data = dataset, x = 'NACE_first', y = 'employee_points', palette = 'Set3', inner = 'quart')
# Set some attributes on the seaborn-object
v.set(ylim=(0,120), xlabel = 'First Nace Number', ylabel = 'Number of Employees per company')
# Remove some of the borders