pandas 从熊猫数据框中按名称绘制正态分布图
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时间：2020-09-14 02:50:00 来源:igfitidea点击:
Normal Distribution Plot by name from pandas dataframe
提问by johnnyb
I have a dataframe like below:
我有一个如下所示的数据框：
dateTime Name DateTime day seconds zscore
11/1/2016 15:17 james 11/1/2016 15:17 Tue 55020 1.158266091
11/1/2016 13:41 james 11/1/2016 13:41 Tue 49260 -0.836236954
11/1/2016 15:17 james 11/1/2016 15:17 Tue 55020 1.158266091
11/1/2016 15:17 james 11/1/2016 15:17 Tue 55020 1.158266091
11/1/2016 15:17 james 11/1/2016 15:17 Tue 55020 1.158266091
11/1/2016 15:17 james 11/1/2016 15:17 Tue 55020 1.158266091
11/1/2016 15:17 james 11/1/2016 15:17 Tue 55020 1.158266091
11/1/2016 15:17 james 11/1/2016 15:17 Tue 55020 1.158266091
11/1/2016 15:17 james 11/1/2016 15:17 Tue 55020 1.158266091
11/1/2016 15:17 james 11/1/2016 15:17 Tue 55020 1.158266091
11/1/2016 15:17 james 11/1/2016 15:17 Tue 55020 1.158266091
11/1/2016 13:41 james 11/1/2016 13:41 Tue 49260 -0.836236954
11/1/2016 13:41 james 11/1/2016 13:41 Tue 49260 -0.836236954
11/1/2016 13:41 james 11/1/2016 13:41 Tue 49260 -0.836236954
11/1/2016 13:41 james 11/1/2016 13:41 Tue 49260 -0.836236954
11/1/2016 13:41 james 11/1/2016 13:41 Tue 49260 -0.836236954
11/1/2016 13:41 james 11/1/2016 13:41 Tue 49260 -0.836236954
11/1/2016 13:41 james 11/1/2016 13:41 Tue 49260 -0.836236954
11/1/2016 13:42 james 11/1/2016 13:42 Tue 49320 -0.81546088
11/1/2016 13:42 james 11/1/2016 13:42 Tue 49320 -0.81546088
11/1/2016 13:42 james 11/1/2016 13:42 Tue 49320 -0.81546088
11/1/2016 13:42 james 11/1/2016 13:42 Tue 49320 -0.81546088
11/1/2016 13:42 james 11/1/2016 13:42 Tue 49320 -0.81546088
11/1/2016 13:42 james 11/1/2016 13:42 Tue 49320 -0.81546088
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:07 matt 11/1/2016 9:07 Tue 32820 -0.223746683
11/1/2016 9:08 matt 11/1/2016 9:08 Tue 32880 -0.111873342
11/1/2016 9:48 matt 11/1/2016 9:48 Tue 35280 4.363060322
zscore is calculated as below:
zscore 计算如下：
grp2 = df.groupby(['Name'])['seconds']
df['zscore'] = grp2.transform(lambda x: (x - x.mean()) / x.std(ddof=1))
I would like to plot my data in a bell curve / normal distribution plot and save this as a picture/pdf file for each Name in my dataframe.
我想在钟形曲线/正态分布图中绘制我的数据，并将其保存为数据框中每个名称的图片/pdf文件。
I have tried to plot the zscores like below:
我试图绘制如下 zscores：
df['by_name'].plot(kind='hist', normed=True)
range = np.arange(-7, 7, 0.001)
plt.plot(range, norm.pdf(range,0,1))
plt.show()
How would I go about plotting the by_name zscores column for each name in my data?
我将如何为数据中的每个名称绘制 by_name zscores 列？
回答by piRSquared
np.random.seed([3,1415])
df = pd.DataFrame(dict(
Name='matt joe adam farley'.split() * 100,
Seconds=np.random.randint(4000, 5000, 400)
))
df['Zscore'] = df.groupby('Name').Seconds.apply(lambda x: x.div(x.mean()))
df.groupby('Name').Zscore.plot.kde()
split out plots
分割地块
g = df.groupby('Name').Zscore
n = g.ngroups
fig, axes = plt.subplots(n // 2, 2, figsize=(6, 6), sharex=True, sharey=True)
for i, (name, group) in enumerate(g):
r, c = i // 2, i % 2
group.plot.kde(title=name, ax=axes[r, c])
fig.tight_layout()
kde+ hist
kde+ hist
g = df.groupby('Name').Zscore
n = g.ngroups
fig, axes = plt.subplots(n // 2, 2, figsize=(6, 6), sharex=True, sharey=True)
for i, (name, group) in enumerate(g):
r, c = i // 2, i % 2
a1 = axes[r, c]
a2 = a1.twinx()
group.plot.hist(ax=a2, alpha=.3)
group.plot.kde(title=name, ax=a1, c='r')
fig.tight_layout()
