[데이터시각화] Matplotlib - Ticks 적용하기

[데이터시각화] Matplotlib - Ticks 적용하기

Ticks

xticks

Get or set the x-limits of the current tick locations and labels.

yticks

Get or set the y-limits of the current tick locations and labels.

plt.yticks([0,1,2], ["one","two","three"])

전체코드

# Scatter plot
plt.scatter(gdp_cap, life_exp)

# Previous customizations
plt.xscale('log') 
plt.xlabel('GDP per Capita [in USD]')
plt.ylabel('Life Expectancy [in years]')
plt.title('World Development in 2007')

# Definition of tick_val and tick_lab
tick_val = [1000,10000,100000]
tick_lab = ['1k','10k','100k']

# Adapt the ticks on the x-axis
plt.xticks(tick_val,tick_lab)

# After customizing, display the plot
plt.show()

 

Size

# Update: set s argument to np_pop
plt.scatter(gdp_cap, life_exp, s = np_pop)

 

Colors

# Specify c and alpha inside plt.scatter()
plt.scatter(x = gdp_cap, y = life_exp, s = np.array(pop) * 2, c=col, alpha=0.8)

# Previous customizations
plt.xscale('log') 
plt.xlabel('GDP per Capita [in USD]')
plt.ylabel('Life Expectancy [in years]')
plt.title('World Development in 2007')
plt.xticks([1000,10000,100000], ['1k','10k','100k'])

# Show the plot
plt.show()

 

Additional Customization

# Scatter plot
plt.scatter(x = gdp_cap, y = life_exp, s = np.array(pop) * 2, c = col, alpha = 0.8)

# Previous customizations
plt.xscale('log') 
plt.xlabel('GDP per Capita [in USD]')
plt.ylabel('Life Expectancy [in years]')
plt.title('World Development in 2007')
plt.xticks([1000,10000,100000], ['1k','10k','100k'])

# Additional customizations
plt.text(1550, 71, 'India')
plt.text(5700, 80, 'China')

# Add grid() call
plt.grid(True)

# Show the plot
plt.show()