【数据分析与可视化】seaborn实现柱状图和热力图

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

from pandas import Series, DataFrame

# 获取在线数据
df = sns.load_dataset('flights')

df.head()

df.shape

(144, 3)

# 透视表(方便看一年的数据)
df = df.pivot(index='month', columns='year', values='passengers')
df

# 热力图(浅部分飞行次数多)
sns.heatmap(df)

<matplotlib.axes._subplots.AxesSubplot at 0x1a1bed4a50>

# df普通线性
df.plot()

<matplotlib.axes._subplots.AxesSubplot at 0x1a1de84e90>

sns.heatmap(df, annot=True, fmt='d')

<matplotlib.axes._subplots.AxesSubplot at 0x1a1e86f710>

# 柱状图 每年飞行总和
s = df.sum()
s

year
1949    1520
1950    1676
1951    2042
1952    2364
1953    2700
1954    2867
1955    3408
1956    3939
1957    4421
1958    4572
1959    5140
1960    5714
dtype: int64

# 横坐标 年份
s.index

Int64Index([1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959,
            1960],
           dtype='int64', name='year')

# 纵坐标 每年总和
s.values

array([1520, 1676, 2042, 2364, 2700, 2867, 3408, 3939, 4421, 4572, 5140,
       5714])

# sns柱状图
sns.barplot(x = s.index, y=s.values)

<matplotlib.axes._subplots.AxesSubplot at 0x1a1f704650>

# 柱状图-普通画 
s.plot(kind="bar")

<matplotlib.axes._subplots.AxesSubplot at 0x1a1f892d10>