Generate Dummy Data With Python

from pandas.util.testing import makeDataFrame

df = makeDataFrame()

import pandas as pd

s = pd.Series(list('abca'))
pd.get_dummies(s)

from random import randint

num_list = 5
num_keys = 3

list_of_dicts = []

for i in range(num_list):
    d = {}
    for j in range(1,num_keys+1):
        d[chr(j+96)]=randint(1,10)
    list_of_dicts.append(d)
list_of_dicts

[{'a': 3, 'b': 8, 'c': 4},
 {'a': 9, 'b': 4, 'c': 2},
 {'a': 9, 'b': 10, 'c': 6},
 {'a': 6, 'b': 4, 'c': 1},
 {'a': 3, 'b': 8, 'c': 3}]

from random import randint

num_keys = 5 
letters = []
for i in range(1,num_keys+1):
    letters.append(chr(i+96))

dict_of_lists = {key: list(range(randint(5,10))) for key in letters}
dict_of_lists

{'a': [0, 1, 2, 3, 4, 5, 6, 7],
 'b': [0, 1, 2, 3, 4, 5, 6],
 'c': [0, 1, 2, 3, 4, 5],
 'd': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
 'e': [0, 1, 2, 3, 4, 5, 6]}

def make_df_from_lists(index,**kwargs):
    return pd.DataFrame(list(zip(*kwargs.values())),index=index,columns=list(kwargs.keys()))

index = ['United States', 'Germany', 'Great Britain', 'Russia', 'China', 'France', 'Australia', 'Italy', 'Canada', 'Japan']

gold = [137, 47, 64, 50, 44, 20, 23, 8, 4, 17]
silver = [52, 43, 55, 28, 30, 55, 34, 38, 4, 13]
bronze = [67, 67, 26, 35, 35, 21, 25, 24, 61, 34]

make_df_from_lists(index,Bronze=bronze,Gold=gold,Silver=silver)

cols,dfs,i,s = ['date','values'], [], 1, 3

for date in ['2022-01-01', '2022-01-02']:
    data = list(zip([date]*s,list(range(i,i+s))))
    dfs.append(pd.DataFrame(data,columns=cols))
    i+=s

import random
import pandas as pd

def random_timeseries(initial_value: float, volatility: float, count: int) -> list:
    time_series = [initial_value, ]
    for _ in range(count):
        time_series.append(time_series[-1] + initial_value * random.gauss(0, 1) * volatility)
    return time_series

ts = pd.date_range(start='2018-01-01', end='2022-01-01', freq='D')
ts = pd.DataFrame(ts, columns=['date'])
ts['values'] = random_timeseries(1.2, 0.15, len(ts)-1)
ts.set_index('date').plot()