Question:
How do I add horizontal lines to a plot
based on the sort_values
criteria specified below captured in the top_5
variable.:
Data:
Here is a slice of the data in a CSV:
This is the current plot.
axnum = today_numBars_slice[['High','Low']].plot()
axnum.yaxis.set_major_formatter(FormatStrFormatter('%.2f'))
This is the data I want to add to this plot (the High
and Low
values from each row):
top_5 = today_numBars_slice[['High','Low','# of Trades']].sort_values(by='# of Trades',ascending=False).head()
top_5
High Low # of Trades
Timestamp
2017-01-02 12:55:09.100 164.88 164.84 470
2017-01-02 12:10:12.000 164.90 164.86 465
2017-01-02 12:38:59.000 164.90 164.86 431
2017-01-02 11:54:49.100 164.87 164.83 427
2017-01-02 10:52:26.000 164.60 164.56 332
Desired output:
This is an example of the desired output showing two of the lines from top_5:
You can use faster DataFrame.nlargest
for top 5
rows and then iterrows
with axhline:
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
df = pd.read_csv('for_stack_nums')
#print (df.head())
top_5 = df[['High','Low','# of Trades']].nlargest(5, '# of Trades')
print (top_5)
High Low # of Trades
94 164.88 164.84 470
90 164.90 164.86 465
93 164.90 164.86 431
89 164.87 164.83 427
65 164.60 164.56 332
axnum = df[['High','Low']].plot()
axnum.yaxis.set_major_formatter(ticker.FormatStrFormatter('%.2f'))
for idx, l in top_5.iterrows():
plt.axhline(y=l['High'], color='r')
plt.axhline(y=l['Low'], color='b')
plt.show()
Also subset is not necessary:
df = pd.read_csv('for_stack_nums.csv')
#print (df.head())
axnum = df[['High','Low']].plot()
axnum.yaxis.set_major_formatter(ticker.FormatStrFormatter('%.2f'))
for idx, l in df.nlargest(5, '# of Trades').iterrows():
plt.axhline(y=l['High'], color='r')
plt.axhline(y=l['Low'], color='b')
plt.show()