Scatter plots in Pandas/Pyplot: How to plot by category [duplicate]

You can use scatter for this, but that requires having numerical values for your key1, and you won't have a legend, as you noticed.

It's better to just use plot for discrete categories like this. For example:

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
np.random.seed(1974)

# Generate Data
num = 20
x, y = np.random.random((2, num))
labels = np.random.choice(['a', 'b', 'c'], num)
df = pd.DataFrame(dict(x=x, y=y, label=labels))

groups = df.groupby('label')

# Plot
fig, ax = plt.subplots()
ax.margins(0.05) # Optional, just adds 5% padding to the autoscaling
for name, group in groups:
    ax.plot(group.x, group.y, marker='o', linestyle='', ms=12, label=name)
ax.legend()

plt.show()

If you'd like things to look like the default pandas style, then just update the rcParams with the pandas stylesheet and use its color generator. (I'm also tweaking the legend slightly):

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
np.random.seed(1974)

# Generate Data
num = 20
x, y = np.random.random((2, num))
labels = np.random.choice(['a', 'b', 'c'], num)
df = pd.DataFrame(dict(x=x, y=y, label=labels))

groups = df.groupby('label')

# Plot
plt.rcParams.update(pd.tools.plotting.mpl_stylesheet)
colors = pd.tools.plotting._get_standard_colors(len(groups), color_type='random')

fig, ax = plt.subplots()
ax.set_color_cycle(colors)
ax.margins(0.05)
for name, group in groups:
    ax.plot(group.x, group.y, marker='o', linestyle='', ms=12, label=name)
ax.legend(numpoints=1, loc='upper left')

plt.show()

This is simple to do with Seaborn (pip install seaborn) as a oneliner

sns.scatterplot(x_vars="one", y_vars="two", data=df, hue="key1") :

import seaborn as sns
import pandas as pd
import numpy as np
np.random.seed(1974)

df = pd.DataFrame(
    np.random.normal(10, 1, 30).reshape(10, 3),
    index=pd.date_range('2010-01-01', freq='M', periods=10),
    columns=('one', 'two', 'three'))
df['key1'] = (4, 4, 4, 6, 6, 6, 8, 8, 8, 8)

sns.scatterplot(x="one", y="two", data=df, hue="key1")

Here is the dataframe for reference:

Since you have three variable columns in your data, you may want to plot all pairwise dimensions with:

sns.pairplot(vars=["one","two","three"], data=df, hue="key1")

https://rasbt.github.io/mlxtend/user_guide/plotting/category_scatter/ is another option.