Python matplotlib/seaborn热图,使用带日期时间索引的熊猫数据框
我的数据框如下所示:Python matplotlib/seaborn热图,使用带日期时间索引的熊猫数据框,python,pandas,matplotlib,heatmap,Python,Pandas,Matplotlib,Heatmap,我的数据框如下所示: timestamp a b c 2018-07-04 08:11:54.170 5.732026 7.930378 8.606152 2018-07-04 08:15:01.910 5.483141 8.040632 8.414517 2018-07-04 08:23:09.700 5.454963 7.634940
timestamp a b c
2018-07-04 08:11:54.170 5.732026 7.930378 8.606152
2018-07-04 08:15:01.910 5.483141 8.040632 8.414517
2018-07-04 08:23:09.700 5.454963 7.634940 8.940616
2018-07-04 08:25:17.490 6.031954 7.256924 8.380531
2018-07-04 08:42:25.290 5.860383 7.488524 8.358526
2018-07-04 09:16:33.300 5.654590 7.697418 8.476449
2018-07-04 09:27:40.830 5.277766 7.817510 8.887601
2018-07-04 09:33:48.620 5.568183 7.752958 9.019584
2018-07-04 09:45:56.410 5.886682 7.326519 8.714343
2018-07-04 09:50:04.200 6.141217 7.462479 8.745352
2018-07-04 10:13:11.950 5.894507 7.515888 8.752824
2018-07-04 10:19:19.740 5.720255 7.387331 8.755654
它有一个包含日期时间戳的索引。其他3列具有浮点值
我想用matplotlib/seaborn创建一个热图,如下所示(请注意x轴):
这张照片是手工编辑的
以下是我的代码片段:
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import matplotlib.dates as mdates
from matplotlib.dates import DayLocator, HourLocator, DateFormatter, drange
import datetime as dt
df = pd.DataFrame()
df['timestamp']=['2018-07-04 08:11:54.170000', '2018-07-04 08:15:01.910000',
'2018-07-04 08:23:09.700000', '2018-07-04 08:25:17.490000',
'2018-07-04 08:42:25.290000', '2018-07-04 09:16:33.300000',
'2018-07-04 09:27:40.830000', '2018-07-04 09:33:48.620000',
'2018-07-04 09:45:56.410000', '2018-07-04 09:50:04.200000',
'2018-07-04 10:13:11.950000', '2018-07-04 10:19:19.740000']
df['a']=[5.732026, 5.483141, 5.454963, 6.031954, 5.860383, 5.654590, 5.277766,
5.568183, 5.886682, 6.141217, 5.894507, 5.720255]
df['b']=[7.930378, 8.040632, 7.634940, 7.256924, 7.488524, 7.697418, 7.817510,
7.752958, 7.326519, 7.462479, 7.515888, 7.387331]
df['c']=[8.606152, 8.414517, 8.940616, 8.380531, 8.358526, 8.476449, 8.887601,
9.019584, 8.714343, 8.745352, 8.752824, 8.755654]
df=df.set_index(['timestamp'])
df.index = pd.to_datetime(df.index)
fig, axHM = plt.subplots(1,1, figsize=(12,2))
xmin=dt.datetime(2018, 7, 4, 8, 0, 0)
xmax=dt.datetime(2018, 7, 4, 10, 30, 0)
axHM.set_xticks(drange(xmin, xmax, dt.timedelta(minutes=10)))
myXAxisDate = mdates.DateFormatter('%H:%M')
axHM.xaxis.set_major_formatter(myXAxisDate)
axHM = sns.heatmap(df.T, cmap='coolwarm')
它只会产生这种糟糕的结果:
问题是,我正在与xticks斗争。如果有一个使用matplotlib的解决方案就好了。提前非常感谢 最后两行怎么样:
plt.xticks(rotation=45)
axHM = sns.heatmap(df.T, cmap='coolwarm', xticklabels=df.index.strftime('%H:%M'))
忘掉matplotlib。。。仔细看一看,这将使你达到你的目标
import pandas as pd
from plotly import __version__
from plotly.offline import init_notebook_mode, plot, iplot
import plotly.graph_objs as go
init_notebook_mode(connected=True)
df = pd.DataFrame()
df['timestamp']=['2018-07-04 08:11:54.170000', '2018-07-04 08:15:01.910000',
'2018-07-04 08:23:09.700000', '2018-07-04 08:25:17.490000',
'2018-07-04 08:42:25.290000', '2018-07-04 09:16:33.300000',
'2018-07-04 09:27:40.830000', '2018-07-04 09:33:48.620000',
'2018-07-04 09:45:56.410000', '2018-07-04 09:50:04.200000',
'2018-07-04 10:13:11.950000', '2018-07-04 10:19:19.740000']
df['a']=[5.732026, 5.483141, 5.454963, 6.031954, 5.860383, 5.654590, 5.277766,
5.568183, 5.886682, 6.141217, 5.894507, 5.720255]
df['b']=[7.930378, 8.040632, 7.634940, 7.256924, 7.488524, 7.697418, 7.817510,
7.752958, 7.326519, 7.462479, 7.515888, 7.387331]
df['c']=[8.606152, 8.414517, 8.940616, 8.380531, 8.358526, 8.476449, 8.887601,
9.019584, 8.714343, 8.745352, 8.752824, 8.755654]
df=df.set_index(['timestamp'])
df.index = pd.to_datetime(df.index)
z = []
z.append(list(df['c']))
z.append(list(df['b']))
z.append(list(df['a']))
data = [
go.Heatmap(
z=z,
x=df.index,
y=['c','b','a'],
)
]
layout = go.Layout(
xaxis = dict(ticks='', nticks=25),
yaxis = dict(ticks='' )
)
fig = go.Figure(data=data, layout=layout)
iplot(fig)
玩得开心!
您可以了解如何在matplotlibSee中设置日期格式。也许,您可以采用该示例。您留下了一些未使用的导入