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# Pivot the DF so that there's a column for each month, each row\
# represents a year, and the cells have the mean page views for the\
# respective year and month
df_pivot = pd.pivot_table(
	df,
	values="page_views",
	index="year",
	columns="month",
	aggfunc=np.mean
)

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import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

# Load the CSV (load date data as proper date types)
df = pd.read_csv("page_views.csv")
df["date"] = pd.to_datetime(df["date"])
# Sort the DF from oldest to most recent recordings
df.sort_values(by="date", inplace=True)
# Use the column of dates as the DF's index

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0.70 - Coffee
0.75 - Cake slice
19.99 - Video game
12 - Lunch
6.99 - Spotify monthly charge
22.24 - Travel mug
7 - Cinema ticket
15 - Lunch
Total: 85.62

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import re
import datetime
import pandas as pd

PATTERN = r'(^([\d]+)([\.]?)([\d]*))( - )(.*)'

# Load text
with open("expenses.txt", "r") as f:
	expenses_txt = f.readlines()
# Put all the lines into a single string

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import pandas as pd
import numpy as np

# Current employee dataset
original = pd.DataFrame({
	"id": [1, 2, 3, 4], 
	"name": ["Michael", "Jim", "Pam", "Dwight"], 
	"age": [46, 35, 35, 38],
	"email": ["michael@dundermifflin.com", "jim@dundermifflin.com", "pam@dundermifflin.com", "dwight@dundermifflin.com"],
	"in_company": [True, True, True, True]

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def get_text_dimensions(text_string, font):
    # https://stackoverflow.com/a/46220683/9263761
    ascent, descent = font.getmetrics()

    text_width = font.getmask(text_string).getbbox()[2]
    text_height = font.getmask(text_string).getbbox()[3] + descent

    return (text_width, text_height)

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from PIL import Image, ImageDraw, ImageFont
from textwrap import wrap

def get_y_and_heights(text_wrapped, dimensions, margin, font):
    """Get the first vertical coordinate at which to draw text and the height of each line of text"""
    # https://stackoverflow.com/a/46220683/9263761
    ascent, descent = font.getmetrics()

    # Calculate the height needed to draw each line of text (including its bottom margin)
    line_heights = [

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from configparser import ConfigParser
import psycopg2
import psycopg2.extras as psql_extras
import pandas as pd
from typing import Dict, List


def load_connection_info(
    ini_filename: str
) -> Dict[str, str]:

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from configparser import ConfigParser
import psycopg2
import psycopg2.extras as psql_extras
import pandas as pd
from typing import Dict


def load_connection_info(
    ini_filename: str
) -> Dict[str, str]:

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from configparser import ConfigParser
import psycopg2
from typing import Dict


def load_connection_info(
    ini_filename: str
) -> Dict[str, str]:
    parser = ConfigParser()
    parser.read(ini_filename)