Last active
February 24, 2023 06:36
-
-
Save yosukesan/74bcc9028860254f6dd1b4bf8f774bac to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import matplotlib.pyplot as plt | |
import pandas as pd | |
import datetime as dt | |
df = pd.DataFrame(columns=['Sales'], | |
index=[dt.datetime(2022,1,1), dt.datetime(2022,1,2), dt.datetime(2022,1,3), dt.datetime(2022,1,4)]) | |
df['Sales'] = [100,200,500,-100] | |
df['Change in %'] = df.pct_change() | |
#df = df.fillna(0) | |
print(df) | |
import matplotlib.pyplot as plt | |
fig, ax = plt.subplots() | |
plt.xticks(rotation=60) | |
ax.bar(df.index, df['Sales'], alpha=0.5) | |
ax.set_ylabel('Sales') | |
ax2 = ax.twinx() | |
ax2.plot(df['Change in %'], 'o-', color='red') | |
for x, y in zip(df.index, df['Change in %']): | |
ax2.text(x, y+y*0.1, y) | |
for x, y in zip(df.index, df['Sales']): | |
ax.text(x-dt.timedelta(hours=8), y-y*0.3, y, color='white') | |
plt.show() |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment