Thiagobc23

# countries from https://data.worldbank.org/country
all_countries = ['Afghanistan', 'Albania', 'Algeria', 'American Samoa', 
                 'Andorra', 'Angola', 'Antigua and Barbuda', 'Argentina', 
                 'Armenia', 'Aruba', 'Australia', 'Austria', 'Azerbaijan', 
                 'Bahamas, The', 'Bahrain', 'Bangladesh', 'Barbados', 
                 'Belarus', 'Belgium', 'Belize', 'Benin', 'Bermuda', 
                 'Bhutan', 'Bolivia', 'Bosnia and Herzegovina', 'Botswana', 
                 'Brazil', 'British Virgin Islands', 'Brunei Darussalam', 
                 'Bulgaria', 'Burkina Faso', 'Burundi', 'Cabo Verde', 
                 'Cambodia', 'Cameroon', 'Canada', 'Cayman Islands', 

Thiagobc23

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Patch
from pandas import Timestamp

##### DATA #####
data = {'Task': {0: 'TSK M',
                 1: 'TSK N',
                 2: 'TSK L',

Thiagobc23

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Patch
from pandas import Timestamp

##### DATA #####
data = {'Task': {0: 'TSK M',
                 1: 'TSK N',
                 2: 'TSK L',

Thiagobc23

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy import interpolate

url = 'https://gist.githubusercontent.com/Thiagobc23/4ccb4ea1c612d9d68921bf990ce28855/raw/6225824a6b7d5d273019c09c25cbbaa5b82009bc/dummy_data.csv'
df = pd.read_csv(url, index_col='ID')

# figure
fig, ax = plt.subplots(1, figsize=(12,4), facecolor='#293952')

Thiagobc23

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

url = 'https://gist.githubusercontent.com/Thiagobc23/4ccb4ea1c612d9d68921bf990ce28855/raw/6225824a6b7d5d273019c09c25cbbaa5b82009bc/dummy_data.csv'
df = pd.read_csv(url, index_col='ID')

# figure
fig, ax = plt.subplots(1, figsize=(12,4), facecolor='#293952')
ax.set_facecolor('#293952')

Thiagobc23

import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
import numpy as np
import pandas as pd

url = 'https://gist.githubusercontent.com/Thiagobc23/4ccb4ea1c612d9d68921bf990ce28855/raw/6225824a6b7d5d273019c09c25cbbaa5b82009bc/dummy_data.csv'
df = pd.read_csv(url, index_col='ID')

# figure
# data

Thiagobc23

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd

# DATA
url = 'https://gist.githubusercontent.com/Thiagobc23/4ccb4ea1c612d9d68921bf990ce28855/raw/07af955c17d1816aba58dea74d65f60210702a15/film.csv'
df = pd.read_csv(url, index_col='ID')

# Theme
sns.set_theme(style="white", rc={"axes.facecolor": (0, 0, 0, 0), 'axes.linewidth':2})

Thiagobc23

from math import pi
import numpy as np
from matplotlib.patches import Patch
from matplotlib.lines import Line2D

# data and variables
data = [82, 75, 91]
startangle = 90
colors = ['#4393E5', '#43BAE5', '#7AE6EA']

Thiagobc23

import matplotlib.pyplot as plt

data = [87,13]

fig, ax = plt.subplots(figsize=(6, 6))

wedgeprops = {'width':0.3, 'edgecolor':'black', 'linewidth':3}
ax.pie(data, wedgeprops=wedgeprops, startangle=90, colors=['#5DADE2', '#515A5A'])

plt.title('Worldwide Access to Electricity', fontsize=24, loc='left')

Thiagobc23