我有一个数据框架,有两列这样的(以日期为索引)。
我的目标是像这样用seaborn绘制条形图(用excel)。
我遵循这里的讨论。在这里输入链接描述
我知道,我必须使用熔体.但当我把下面的代码的结果是索引(日期)消失(由数字取代)和数据框架结构改变这样的。
# pd.melt(df, id_vars=['A'], value_vars=['B'])
premier_melt = pd.melt(final_mada_df,id_vars=["Confirmed"],value_vars = ["Recovered"])
我们怎样才能解决这种问题,正确地用seaborn绘制条形图呢?
先谢谢
我把下面的代码按照下面的建议。
# main dataframe
df2
Recovered Confirmed
3/20/20 0 3
3/21/20 0 0
3/22/20 0 0
3/23/20 0 9
df2.stack()
out :
3/20/20 Recovered 0
Confirmed 3
3/21/20 Recovered 0
Confirmed 0
3/22/20 Recovered 0
..
5/4/20 Confirmed 0
5/5/20 Recovered 2
Confirmed 2
5/6/20 Recovered 0
Confirmed 7
Length: 96, dtype: int64
df2.rename(columns={'level_1':'Status',0:'Values'})
out:
Recovered Confirmed
3/20/20 0 3
3/21/20 0 0
3/22/20 0 0
3/23/20 0 9
3/24/20 0 5
但当我把下面的代码,有一个错误。
# plot
ax = sns.barplot(x=df2.index,y='Values',data=df2,hue='Status')
ValueError: Could not interpret input 'Values'
.stack()
,如下图所示。import pandas as pd
import seaborn as sns
import numpy as np
from datetime import datetime
import matplotlib.pyplot as plt
# optional graph format parameters
plt.rcParams['figure.figsize'] = (16.0, 10.0)
plt.style.use('ggplot')
# data
np.random.seed(365)
data = {'Confirmed': [np.random.randint(10) for _ in range(25)],
'date': pd.bdate_range(datetime.today(), freq='d', periods=25).tolist()}
# dataframe
df = pd.DataFrame(data)
# add recovered
df['Recovered'] = df['Confirmed'].div(2)
| date | Confirmed | Recovered |
|:--------------------|------------:|------------:|
| 2020-05-12 00:00:00 | 4 | 2 |
| 2020-05-13 00:00:00 | 1 | 0.5 |
| 2020-05-14 00:00:00 | 5 | 2.5 |
| 2020-05-15 00:00:00 | 1 | 0.5 |
| 2020-05-16 00:00:00 | 9 | 4.5 |
# verify datetime format and set index
df.date = pd.to_datetime(df.date)
df.set_index('date', inplace=True)
df1 = df.stack().reset_index().set_index('date').rename(columns={'level_1': 'Status', 0: 'Values'})
| date | Status | Values |
|:--------------------|:----------|---------:|
| 2020-05-23 00:00:00 | Confirmed | 2 |
| 2020-05-23 00:00:00 | Recovered | 1 |
| 2020-05-24 00:00:00 | Confirmed | 4 |
| 2020-05-24 00:00:00 | Recovered | 2 |
| 2020-05-25 00:00:00 | Confirmed | 1 |
df
不 df1
. 如上图所示,每个日期都会重复,所以 df1.index.to_series()
将产生一个日期重复的列表。ax = sns.barplot(x=df1.index, y='Values', data=df1, hue='Status')
# format the x-axis tick labels uses df, not df1
ax.xaxis.set_major_formatter(plt.FixedFormatter(df.index.to_series().dt.strftime("%Y-%m-%d")))
# alternative use the following to format the labels
# _, labels = plt.xticks()
# labels = [label.get_text()[:10] for label in labels]
# ax.xaxis.set_major_formatter(plt.FixedFormatter(labels))
plt.xticks(rotation=90)
plt.show()
df.plot.bar()
df1
df
有一个日期时间指数,它被认为是x轴,所有的列都被绘制在y轴上。ax = df.plot.bar()
ax.xaxis.set_major_formatter(plt.FixedFormatter(df.index.to_series().dt.strftime("%Y-%m-%d")))
plt.show()