【数据分析与可视化】seaborn实现柱状图和热力图

在线加载数据

https://github.com/mwaskom/seaborn

解决数据不存在

【解决sns加载数据报错】sns.load_dataset(“xxx”)报错

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()

	year	month	passengers
0	1949	January	112
1	1949	February	118
2	1949	March	132
3	1949	April	129
4	1949	May	121

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

year	1949	1950	1951	1952	1953	1954	1955	1956	1957	1958	1959	1960
month
January	112	115	145	171	196	204	242	284	315	340	360	417
February	118	126	150	180	196	188	233	277	301	318	342	391
March	132	141	178	193	236	235	267	317	356	362	406	419
April	129	135	163	181	235	227	269	313	348	348	396	461
May	121	125	172	183	229	234	270	318	355	363	420	472
June	135	149	178	218	243	264	315	374	422	435	472	535
July	148	170	199	230	264	302	364	413	465	491	548	622
August	148	170	199	242	272	293	347	405	467	505	559	606
September	136	158	184	209	237	259	312	355	404	404	463	508
October	119	133	162	191	211	229	274	306	347	359	407	461
November	104	114	146	172	180	203	237	271	305	310	362	390
December	118	140	166	194	201	229	278	306	336	337	405	432

# 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>