moritzkoerber

import pandas as pd
from sklearn.compose import ColumnTransformer
from sklearn.impute import SimpleImputer
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import classification_report
from sklearn.model_selection import GridSearchCV, RepeatedStratifiedKFold
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import OneHotEncoder, StandardScaler

titanic = pd.read_csv('./titanic.csv')

moritzkoerber

import pandas as pd
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import GridSearchCV, RepeatedStratifiedKFold
from sklearn.pipeline import Pipeline
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import OneHotEncoder, StandardScaler
from sklearn.metrics import f1_score, classification_report
from sklearn.impute import SimpleImputer
from sklearn.model_selection import train_test_split

moritzkoerber

Keybase proof

I hereby claim:

• I am moritzkoerber on github.
• I am moritzkoerber (https://keybase.io/moritzkoerber) on keybase.
• I have a public key ASBagXNuNawc5COk1wSUH57zvRWiy4bM8o7ZeCxKWVv06Ao

To claim this, I am signing this object:

moritzkoerber

import argparse
import pickle
import string
import sys

import nltk
import pandas as pd
from nltk.corpus import stopwords
from nltk.stem.wordnet import WordNetLemmatizer
from nltk.tokenize import word_tokenize

moritzkoerber

import pandas as pd

df = pd.DataFrame(
    dict(temperature=[24, 26, 28], ice_cream_cones=[14, 20, 23], drinks=[18, 22, 28])
)

moritzkoerber

import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(
    go.Scatter(
        x=df.temperature,
        y=df.ice_cream_cones,
        name="Ice Cream",
        marker_color="#2457BD",

moritzkoerber

fig.update_layout(
    updatemenus=[
        dict(
            type="buttons",
            direction="right",
            x=0.7,
            y=1.2,
            showactive=True,
            buttons=list(
                [

moritzkoerber

df["scoops"] = df["ice_cream_cones"] * 2

fig.update_layout(
    updatemenus=[
        dict(
            type="buttons",
            direction="right",
            x=0.7,
            y=1.2,
            showactive=True,

moritzkoerber

def convert_to_sixpack(x):
    return x / 6


fig.update_layout(
    updatemenus=[
        dict(
            type="buttons",
            direction="right",
            x=0.7,

moritzkoerber

import pandas as pd

df = pd.DataFrame(
    dict(
        week=[1, 1, 2, 2, 3, 3] * 2,
        layout=["classic", "classic", "modern", "modern"] * 3,
        response=["conversion", "exit"] * 6,
        cnt=[26, 23, 45, 34, 55, 44, 53, 27, 28, 25, 30, 34],
    )
)