Change values on y axis with matplotlib (3 graphs within 1 plot)-CodePudding

Hello I want to change the highlighted values at y axis from 0 to 10.000.000 with an incrementation of 1.000.000, first here's the data

and here's the plot

I don't know how to change the y ticklabel (because there are 3 graphs within the plot) the and most of the examples on the internet use variable and not dataframe, here's the code, should I use numpy and input the value to a variable?

plt.figure(figsize=(15,4))
#ax.ticklabel_format(style='plain')
#plt.ticklabel_format(useOffset=None)
plt.plot(df['MONTH'], df['MONTHLY INCOME'])
plt.plot(df['MONTH'], df['MONTHLY EXPENSES'])
plt.plot(df['MONTH'], df['MONTHLY SAVINGS'])
plt.ylabel("Dollar")
plt.xlabel("Month")

plt.legend(legend_labels)

CodePudding user response：

you can do this:

plt.yticks(np.arange(0,11e6,1e6),np.arange(0,11e6,1e6))

The first arguments sets the position of the tick, the second one is cast into string, so it is the label. You could also do something like:

plt.yticks(np.arange(0,11e6,1e6),[str(x) 'M' for x in np.arange(0,11,1)])

See that you need 11 instead of 10 just to add the last tick, you could also do it with linspace.

CodePudding user response：

You were almost right, you have to set major formatter to ScalarFormatter before using ax.ticklabel_format(style='plain')

import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter

months = ["January",
          "February",
          "March",
          "April"
          "May",
          "June",
          "July",
          "August",
          "September",
          "October",
          "November",
          "December"]
df = pd.DataFrame({
    'month': months,
    'monthly income': [i*10**6 for i in range(len(months)-1, -1, -1)],
    'monthly expenses': [i*.9*10**6 for i in range(len(months)-1, -1, -1)]
})

df['monthly savings'] = df['monthly income'] - df['monthly expenses']

fig, ax = plt.subplots(figsize=(15, 4))

ax.yaxis.set_major_formatter(ScalarFormatter())
ax.ticklabel_format(style='plain')

legend_labels = df.columns[1:]
for label in legend_labels:
    ax.plot(df['month'], df[label])

ax.set_ylabel("Dollar")
ax.set_xlabel("Month")
ax.legend(legend_labels)