Scatter plot

import pandas as pd
import numpy as np


#import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns


import warnings; warnings.filterwarnings(action='once')

large = 22; med = 16; small = 12
params = {'axes.titlesize': large,
          'legend.fontsize': med,
          'figure.figsize': (16, 10),
          'axes.labelsize': med,
          'axes.titlesize': med,
          'xtick.labelsize': med,
          'ytick.labelsize': med,
          'figure.titlesize': large}
plt.rcParams.update(params)
plt.style.use('seaborn-whitegrid')
sns.set_style("white")
%matplotlib inline

load data

df_gold=pd.read_csv('data/GC=F.csv', sep='|')
df_sp500=pd.read_csv('data/^GSPC.csv', sep='|')

df_gold.head(2)
Date Open High Low Close Volume Dividends Stock Splits
0 2000-08-30 273.899994 273.899994 273.899994 273.899994 0 0 0
1 2000-08-31 274.799988 278.299988 274.799988 278.299988 0 0 0 
df_sp500.head(2)
Date Open High Low Close Volume Dividends Stock Splits
0 1950-01-03 16.66 16.66 16.66 16.66 1260000 0 0
1 1950-01-04 16.85 16.85 16.85 16.85 1890000 0 0 
#combine data
combine=df_gold[['Date', 'Close']].merge(df_sp500[['Date', 'Close']], on=['Date'], how='inner')

combine.head()
Date Close_x Close_y
0 2000-08-30 273.899994 1502.589966
1 2000-08-31 278.299988 1517.680054
2 2000-09-01 277.000000 1520.770020
3 2000-09-05 275.799988 1507.079956
4 2000-09-06 274.200012 1492.250000 
combine.columns=['date', 'gold_price','sp500_price']

combine.head(2)
date gold_price sp500_price
0 2000-08-30 273.899994 1502.589966
1 2000-08-31 278.299988 1517.680054 
x=combine['gold_price']
y=combine['sp500_price']

Plot the graph

plt.figure(figsize=(16,10), dpi= 80)
plt.scatter(x=x, y=y,s=20, c='#8C4660')

# Decorations
plt.gca().set(#xlim=(0.0, 0.1), ylim=(0, 90000),
              xlabel='Area', ylabel='Population')

plt.xticks(fontsize=12); plt.yticks(fontsize=12)
plt.title("Scatterplot of Midwest Area vs Population", fontsize=22) 
plt.show()

png