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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')
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

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To claim this, I am signing this object:

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",
fig.update_layout(
updatemenus=[
dict(
type="buttons",
direction="right",
x=0.7,
y=1.2,
showactive=True,
buttons=list(
[
import pandas as pd
df = pd.DataFrame(
dict(temperature=[24, 26, 28], ice_cream_cones=[14, 20, 23], drinks=[18, 22, 28])
)
def convert_to_sixpack(x):
return x / 6
fig.update_layout(
updatemenus=[
dict(
type="buttons",
direction="right",
x=0.7,
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
moritzkoerber / model_training_for_text_analysis.py
Last active March 8, 2021 08:30
Trains a model to analyze text messages.
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
import yaml
import great_expectations as ge
import os
from great_expectations.cli.datasource import sanitize_yaml_and_save_datasource
from great_expectations.core.batch import BatchRequest
from great_expectations.core.expectation_configuration import ExpectationConfiguration
from contextlib import suppress
project_dir = f"{os.getcwd()}/own_de_project/great_expectations"