How can I add data points to my line plot in same colour (matplotlib)?

Question

I have a line plot to which I would like to add original datapoints in the same colour as the lines (which are fine in default). Problem: When I do it for a lot of IDs or datapoints (also missings) I can no longer distinguish to whom that data belong.

import pandas as pd
df = pd.DataFrame({'year': ['1988', '1989', '1990', '1988', '1989', '1990', '1988', '1989', '1990'],
                   'id': ['1', '1', '1', '2', '2', '2', '3', '3', '3'],
                   'money': ['5', '7', '8', '8', '3', '3', '7', '8', '10']}).astype(int)

import matplotlib.pyplot as plt
import numpy as np
fig, ax = plt.subplots()

for i in df.id.unique():
    df[df['id']==i].plot.line(x='year', y='money', ax=ax, label='id = %s'%i)
    df[df['id']==i].plot.scatter(x='year', y='money', ax=ax)
    plt.xticks(np.unique(df.year))

Question: How can I access the default color list of my plot.line to use it in plot.scatter? Or is there another, easier way to highlight the data which constitutes the lines?

This will change everything from all-blue in all-red. I need the same colours as given by plot.line default to distinguish my cases. regards — Marco
– Marco, Commented Jun 19, 2019 at 13:58

Quang Hoang · Accepted Answer · 2019-06-19 14:02:52Z

2

There's a marker option in plot.line:

fig, ax = plt.subplots()

for i in df.id.unique():
    df[df['id']==i].plot.line(x='year', 
                              y='money', 
                              marker='o', # this add the data points on the line, with the same color 
                              ax=ax, 
                              label='id = %s'%i)

Output:

answered Jun 19, 2019 at 14:02

Quang Hoang

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2 Comments

Sheldore Over a year ago

The marker is not shown in the first two legend entries?

Quang Hoang Over a year ago

@Sheldore Interestingly, no. They only show with a call of plt.legend(). A bug maybe?

Scott Boston · Accepted Answer · 2019-06-19 14:08:53Z

2

IIUC, you can try, although @QuangHoang is the better solution:

import pandas as pd
df = pd.DataFrame({'year': ['1988', '1989', '1990', '1988', '1989', '1990', '1988', '1989', '1990'],
                   'id': ['1', '1', '1', '2', '2', '2', '3', '3', '3'],
                   'money': ['5', '7', '8', '8', '3', '3', '7', '8', '10']}).astype(int)

import matplotlib.pyplot as plt
import numpy as np
fig, ax = plt.subplots()

color = plt.rcParams['axes.prop_cycle'].by_key()['color']

for i in df.id.unique():
    df[df['id']==i].plot.line(x='year', y='money', ax=ax, label='id = %s'%i)
    df[df['id']==i].plot.scatter(x='year', y='money', ax=ax, color=color[i-1])
    plt.xticks(np.unique(df.year))

Output:

answered Jun 19, 2019 at 14:08

Scott Boston

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2 Comments

Quang Hoang Over a year ago

Good to know how to access the color sequence. Although, the color=color[i-1] only works if df.id.unique() == (1,2,3) like this special case.

Scott Boston Over a year ago

Yes, That is true, it is better to use enumerate.

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