Change color at certain bar labels with barplot in matplotlib-CodePudding

I try to plot a bar graph with certain colors to labels and make legend with color for each type. For example, labels "Type 1", "Type 2" and "Type 3" each color corresponding to each label. Thanks!

import matplotlib.pyplot as plt
import pandas as pd
mdict={"Types":["A","B","C","D","F", "G"],"Count":[3,4,5,6,7,6]}
df=pd.DataFrame(mdict)

fig, ax=plt.subplots(figsize=(15,8))

for i in df.Types:
    if i in ["A","B"]:
        ax.bar(df.Types,df.Count,color="red", label="Type 1")
    elif i in ["C","D"]:
        ax.bar(df.Types,df.Count,color="green", label="Type 2")
    else:
        ax.bar(df.Types,df.Count, color="blue", label="Type 3")
ax.legend()

CodePudding user response：

You could add an extra column for the labels, and use seaborn to create the plot:

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd

mdict = {"Types": ["A", "B", "C", "D", "F", "G"], "Count": [3, 4, 5, 6, 7, 6]}
df = pd.DataFrame(mdict)

df["Label"] = "Type 3"
df.loc[df["Types"].isin(["A", "B"]), "Label"] = "Type 1"
df.loc[df["Types"].isin(["C", "D"]), "Label"] = "Type 2"

fig, ax = plt.subplots(figsize=(15, 8))
palette = {"Type 1": "crimson", "Type 2": "limegreen", "Type 3": "dodgerblue"}
sns.barplot(data=df, x="Types", y="Count", hue="Label", palette=palette, dodge=False, ax=ax)
plt.show()

An alternative approach, without seaborn, creates two columns: one for labels and one for a numeric index. Recent matplotlib versions accept a data= keyword, to indicate a dataframe (or a subset of a dataframe). A numeric index is needed to draw the bars at the correct positions.

import matplotlib.pyplot as plt
import pandas as pd

mdict = {"Types": ["A", "B", "C", "D", "F", "G"], "Count": [3, 4, 5, 6, 7, 6]}
df = pd.DataFrame(mdict)

df["Label"] = ["Type 1" if i in ["A", "B"] else "Type 2" if i in ["C", "D"] else "Type 3" for i in df["Types"]]
df["ind"] = range(len(df))

fig, ax = plt.subplots(figsize=(15, 8))
ax.bar("ind", "Count", color="crimson", label="Type 1",
       data=df.loc[df["Types"].isin(["A", "B"])])
ax.bar("ind", "Count", color="limegreen", label="Type 2",
       data=df.loc[df["Types"].isin(["C", "D"])])
ax.bar("ind", "Count", color="dodgerblue", label="Type 2",
       data=df.loc[~ (df["Types"].isin(["A", "B"]) | df["Types"].isin(["C", "D"]))])
ax.set_xticks(df["ind"], df["Types"])
ax.legend()
plt.show()