向Seaborn因子p添加数据标签

Question

我想在Seaborn生成的因子图中添加数据标签。下面是一个例子：

import pandas as pd
from pandas import Series, DataFrame
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline

titanic_df = pd.read_csv('train.csv')
sns.factorplot('Sex',data=titanic_df,kind='count')

如何将“count”值添加到图表上每个栏的顶部？

Answer 1

以上来自@nickil maveli的回答非常好。 这只是为了在向barplot添加数据标签时（按照@user27074的注释中的要求）添加一些参数的清晰性

 # loop through all bars of the barplot
for nr, p in enumerate(ax.patches):

    # height of bar, which is basically the data value
    height = p.get_height() 

    # add text to specified position
    ax.text(
        # bar to which data label will be added 
        # so this is the x-coordinate of the data label
        nr, 

        # height of data label: height / 2. is in the middle of the bar
        # so this is the y-coordinate of the data label
        height / 2., 

        # formatting of data label
        u'{:0.1f}%'.format(height), 

        # color of data label
        color='black', 

        # size of data label
        fontsize=18, 

        # horizontal alignment: possible values are center, right, left
        ha='center', 

        # vertical alignment: possible values are top, bottom, center, baseline
        va='center'
    )

Answer 2

你可以做些更简单的事

plt.figure(figsize=(4, 3))
plot = sns.catplot(x='Sex', y='count', kind='bar', data=titanic_df)

# plot.ax gives the axis object
# plot.ax.patches gives list of bars that can be access using index starting at 0

for i, bar in enumerate(plot.ax.patches):
    h = bar.get_height()
    plot.ax.text(
        i, # bar index (x coordinate of text)
        h+10, # y coordinate of text
        '{}'.format(int(h)),  # y label
        ha='center', 
        va='center', 
        fontweight='bold', 
        size=14)

Answer 3

你可以这样做：

import math
# Set plotting style
sns.set_style('whitegrid')

# Rounding the integer to the next hundredth value plus an offset of 100
def roundup(x):
    return 100 + int(math.ceil(x / 100.0)) * 100 

df = pd.read_csv('train.csv')
sns.factorplot('Sex', data=df, kind='count', alpha=0.7, size=4, aspect=1)

# Get current axis on current figure
ax = plt.gca()

# ylim max value to be set
y_max = df['Sex'].value_counts().max() 
ax.set_ylim([0, roundup(y_max)])

# Iterate through the list of axes' patches
for p in ax.patches:
    ax.text(p.get_x() + p.get_width()/2., p.get_height(), '%d' % int(p.get_height()), 
            fontsize=12, color='red', ha='center', va='bottom')

plt.show()