[Visualization] matplotlib

Bitcoin.csv

0.21MB

 

 

 

데이터 출처:

https://www.kaggle.com/datasets/yasserh/bitcoin-prices-dataset?resource=download

 

 

matplotlib tutorial

https://matplotlib.org/stable/tutorials/introductory/usage.html

 

In [37]:

import matplotlib.pyplot as plt
import seaborn as sns # bulit on top of matplotlib
import pandas as pd
import numpy as np
%matplotlib inline

 

In [38]:

plt.plot([1,2,3,4,5,6], [9,7,8,2,4,6])

 

Out[38]:

[<matplotlib.lines.Line2D at 0x7f1c73ce51c0>]

 

 

 

axes

https://matplotlib.org/stable/gallery/subplots_axes_and_figures/subplots_demo.html

 

In [39]:

 fig, axs = plt.subplots(2, 2)

 

 

 

In [40]:

x = np.linspace(0, 1, 50) # sample

fig, axs = plt.subplots(1, 2, figsize=(10,5))
axs[0].plot(x, x, label = 'linear')
axs[1].plot(x, x**2, label = 'quadratic')

 

Out[40]:

[<matplotlib.lines.Line2D at 0x7f1c73b8b640>]

 

 

In [41]:

x = np.linspace(0, 1, 50) # sample

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10,5))
ax1.plot(x, x, label = 'linear')
ax2.plot(x, x**3, label = 'cubic')

 

Out[41]:

[<matplotlib.lines.Line2D at 0x7f1c73ac0fd0>]

 

 

 

barplot

 

In [42]:

data = [50, 100, 150, 200, 250 ]
plt.bar(range(len(data)), data, color = 'b')

 

Out[42]:

<BarContainer object of 5 artists>

 

 

 

stacked bar chart

 

In [43]:

plt.style.use('ggplot')
labels = ['Test 1', 'Test 2', 'Test 3', 'Test 4', 'Test 5', 'Test 6',]

price_one = [10, 20, 30, 40, 20, 10]
price_two = [10, 20, 50, 40, 30, 20]
tax_one = [1,2,1,2,1,1]
tax_two = [3,4,3,4,3,4]
width = 0.50

# stacked bar visualization
fig, ax = plt.subplots()
ax.bar(labels, price_one, width, align = 'edge', yerr=tax_one, label='First Label')
ax.bar(labels, price_two, width, align = 'edge', yerr=tax_two, bottom=price_one, label='Second Label')
# align : x축 좌표에 정렬( 'center', 'edge' )
# yerr : y축 error bar

ax.set_ylabel('Value')
ax.set_title('Scores by Group')
plt.xticks(rotation='45')
ax.legend()
plt.show()

 

 

 

 

axs 하위 plot 설정

https://pythonguides.com/matplotlib-rotate-tick-labels/

https://www.geeksforgeeks.org/how-to-rotate-x-axis-tick-label-text-in-matplotlib/

 

In [44]:

plt.style.use('ggplot')

data = {'Snack':20, "beverages":10, 'meat': 25, 'vegetable': 15}
names = list(data.keys())
values = list(data.values())

fig, axs = plt.subplots(1,3, figsize=(8,8), sharey=True)

axs[0].bar(names, values)
axs[0].set_xticklabels(ax.get_xticks(), rotation = 50)
axs[1].scatter(names, values)
axs[1].set_xticklabels(ax.get_xticks(), rotation = 50)
axs[2].plot(names, values)
fig.suptitle('Plotting')
plt.xticks(rotation=45)

 

Out[44]:

([0, 1, 2, 3], <a list of 4 Text major ticklabel objects>)

 

 

In [45]:

plt.style.use('dark_background')

x = np.linspace(2, 10 * np.pi, 50)
y = np.sin(x ** 2)

fig, axs = plt.subplots(2)
axs[0].plot(x,y, color='white')
axs[1].plot(x,y**2)

 

Out[45]:

[<matplotlib.lines.Line2D at 0x7f1c73848430>]

 

 

 

Practical Example

 

In [46]:

import datetime

 

In [47]:

df = pd.read_csv('Bitcoin.csv')
df.head()

 

Out[47]:

	Date	Open	High	Low	Close	Adj Close	Volume
0	2014-09-17	465.864014	468.174011	452.421997	457.334015	457.334015	21056800
1	2014-09-18	456.859985	456.859985	413.104004	424.440002	424.440002	34483200
2	2014-09-19	424.102997	427.834991	384.532013	394.795990	394.795990	37919700
3	2014-09-20	394.673004	423.295990	389.882996	408.903992	408.903992	36863600
4	2014-09-21	408.084991	412.425995	393.181000	398.821014	398.821014	26580100

 

In [48]:

plt.style.use('ggplot')
ax = df['Volume'].plot.hist()

 

 

 

In [49]:

df['Date'] = pd.to_datetime(df['Date'], format='%Y/%m/%d')

 

In [51]:

df['year'] = df['Date'].dt.year
df['day'] = df["Date"].dt.day

 

In [53]:

df_solution = df[['year', 'day', 'Volume' ]]

 

In [54]:

fig, ax = plt.subplots()
bitcoin_plot = df_solution.plot.scatter(x='year', y='day', c='Volume', colormap='viridis', figsize=(20,10), ax=ax )

 

 

 

In [56]:

from google.colab import files

fig, ax = plt.subplots()
bitcoin_plot = df_solution.plot.scatter(x='year', y='day', c='Volume', colormap='viridis', figsize=(20,10), ax=ax )
plt.savefig('test_matplotlib.png', bbox_inches='tight')
files.download('test_matplotlib.png')