如何以子图的形式绘制数据框中的列 [英] How to plot columns from a dataframe, as subplots
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问题描述
我在这里做错了什么？我想从 df 创建一个新的数据框，并使用Dates作为折线图中每个新创建的数据框（Emins，FTSE，Stoxx和Nikkei）的x轴。 / p>
我有一个名为 df 的数据框，它是从data.xlsx创建的，看起来像这样：
日期ES1 Z 1 VG1 NK1
0 2005-01-04 -0.0126 0.0077 -0.0030 0.0052
1 2005-01-05 -0.0065 -0.0057 0.0007- 0.0095
2 2005-01-06 0.0042 0.0017 0.0051 0.0044
3 2005-01-07 -0.0017 0.0061 0.0010 -0.0009
4 2005-01-11 -0.0065 -0.0040 -0.0147 0.0070
3670 2020-09-16 -0.0046 -0.0065 -0.0003 -0.0009
3671 2020-09-17 -0.0083 -0.0034 -0.0039 -0.0086
3672 2020-09-18 -0.0024 -0.0009 -0.0009 0.0052
3673 2020-09-23 -0.0206 0.0102 0.0022 -0.0013
3674 2020-09-24 0.0021 -0.0136 -0.0073 -0.0116
从 df 创建了4个新的数据框，分别称为Eminis，FTSE，Stoxx和Ni
感谢您的帮助！！
import numpy as np
import matplotlib.pyplot as plt
plt.style.use（'classic'）
df = pd.read_excel（'data.xlsx'）
df = df.rename（columns = {'Dates'：'Date'，'ES1'：'Eminis'，'Z 1'：'FTSE'，'VG1'：'Stoxx'，'NK1'：'Nikkei'， 'TY1'：'Notes'，'G 1'：'Gilts'，'RX1'：'Bunds'，'JB1'：'JGBS'，'CL1'：'Oil'，'HG1'：'Copper'，' S 1'：'Soybeans'，'GC1'：'Gold'，'WILLTIPS'：'TIPS'}）
标头= df。列
Eminis = df [[''Date'，'Eminis' ]]
FTSE = df [[''Date'，'FTSE']]
Stoxx = df [['Date'，'Stoxx']]
Nikkei = df [['Date' ，'Nikkei']]
＃通过plt.subplots（行，列）
图创建多个图，轴= plt.subplots（2,2，figsize =（20,15） ）
x =日期
y1 = Eminis
y2 =票据
y3 = Stoxx
y4 =日经指数
＃每个子图上有一个图b $ b轴[0] [0] .line（x，y1）
axes [0] [1] .line（x，y2）
axes [1] [0] .line（x，y3）
axes [1] [1] .line（x，y4）
plt.legends（）
plt.show（）
解决方案
- 我认为更简洁的选择是不制作多个数据帧，这会造成不必要的工作和复杂性。
- 绘制数据是关于为绘图API整形数据框
- 在这种情况下，更好的选择是使用
我在这里做什么错了？
-
Date未定义为x =日期 -
y2 =注释：注释未定义 -
.line不是plt方法，并导致AttributeError;应该是plt.plot -
y1-y4是DataFrames，但是传递给y轴的plot方法，这会导致TypeError：无法散列的类型：'numpy.ndarray';一栏应该作为y通过。 -
.legends不是方法;它是.legend
- 如果需要的话，必须为每个子图显示图例。
-
Eminis = df [[''Date'，'Eminis']]
FTSE = df [['Date'，'FTSE']]
Stoxx = df [['Date'，'Stoxx']]
Nikkei = df [['Date'，'Nikkei']]
＃通过plt.subplots（rows，columns）创建多个图
图，轴= plt.subplots（2,2，figsize =（20,15））
x = df日期
y1 = Eminis.Eminis
y2 = FTSE.FTSE
y3 = Stoxx.Stoxx
y4 = Nikkei.Nikkei
＃每个子图
轴上有一个图[0] [0] .plot（x，y1， label ='Eminis'）
axis [0] [0] .legend（）
axes [0] [1] .plot（x，y2，label ='FTSE'）
axes [0] [1] .legend（）
轴[1] [0] .plot（x，y3，label ='Stoxx'）
轴[1] [0] .legend（）
轴[1] [1] .plot（x，y4，label ='Nikkei'）
轴[1] [1] .legend（）
plt.show（ ）
What am I doing wrong here? I want to create for new dataframe from df and use Dates as the x-axis in a line chart for each newly created dataframe (Emins, FTSE, Stoxx and Nikkei).
I have a dataframe called df that I created from data.xlsx and it looks like this:
Dates ES1 Z 1 VG1 NK1
0 2005-01-04 -0.0126 0.0077 -0.0030 0.0052
1 2005-01-05 -0.0065 -0.0057 0.0007 -0.0095
2 2005-01-06 0.0042 0.0017 0.0051 0.0044
3 2005-01-07 -0.0017 0.0061 0.0010 -0.0009
4 2005-01-11 -0.0065 -0.0040 -0.0147 0.0070
3670 2020-09-16 -0.0046 -0.0065 -0.0003 -0.0009
3671 2020-09-17 -0.0083 -0.0034 -0.0039 -0.0086
3672 2020-09-18 -0.0024 -0.0009 -0.0009 0.0052
3673 2020-09-23 -0.0206 0.0102 0.0022 -0.0013
3674 2020-09-24 0.0021 -0.0136 -0.0073 -0.0116
From df I created 4 new dataframes called Eminis, FTSE, Stoxx and Nikkei.
Thanks for your help!!!!
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('classic')
df = pd.read_excel('data.xlsx')
df = df.rename(columns={'Dates':'Date','ES1': 'Eminis', 'Z 1': 'FTSE','VG1': 'Stoxx','NK1': 'Nikkei','TY1': 'Notes','G 1': 'Gilts', 'RX1': 'Bunds','JB1': 'JGBS','CL1': 'Oil','HG1': 'Copper','S 1': 'Soybeans','GC1': 'Gold','WILLTIPS': 'TIPS'})
headers = df.columns
Eminis = df[['Date','Eminis']]
FTSE = df[['Date','FTSE']]
Stoxx = df[['Date','Stoxx']]
Nikkei = df[['Date','Nikkei']]
# create multiple plots via plt.subplots(rows,columns)
fig, axes = plt.subplots(2,2, figsize=(20,15))
x = Date
y1 = Eminis
y2 = Notes
y3 = Stoxx
y4 = Nikkei
# one plot on each subplot
axes[0][0].line(x,y1)
axes[0][1].line(x,y2)
axes[1][0].line(x,y3)
axes[1][1].line(x,y4)
plt.legends()
plt.show()
解决方案
- I think the more succinct option is not to make many dataframes, which creates unnecessary work, and complexity.
- Plotting data is about shaping the dataframe for the plot API
- In this case, a better option is to convert the dataframe to a long (tidy) format, from a wide format, using
.stack.- This places all the labels in one column, and the values in another column
- Use
seaborn.relplot, which can create aFacetGridfrom a dataframe in a long format.seabornis a high-level API formatplotlib, and makes plotting much easier.
- If the dataframe contains many stocks, but only a few are to be plotted, they can be selected with Boolean indexing
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
# import data from excel, or setup test dataframe
data = {'Dates': ['2005-01-04', '2005-01-05', '2005-01-06', '2005-01-07', '2005-01-11', '2020-09-16', '2020-09-17', '2020-09-18', '2020-09-23', '2020-09-24'],
'ES1': [-0.0126, -0.0065, 0.0042, -0.0017, -0.0065, -0.0046, -0.0083, -0.0024, -0.0206, 0.0021],
'Z 1': [0.0077, -0.0057, 0.0017, 0.0061, -0.004, -0.0065, -0.0034, -0.0009, 0.0102, -0.0136],
'VG1': [-0.003, 0.0007, 0.0051, 0.001, -0.0147, -0.0003, -0.0039, -0.0009, 0.0022, -0.0073],
'NK1': [0.0052, -0.0095, 0.0044, -0.0009, 0.007, -0.0009, -0.0086, 0.0052, -0.0013, -0.0116]}
df = pd.DataFrame(data)
# rename columns
df = df.rename(columns={'Dates':'Date','ES1': 'Eminis', 'Z 1': 'FTSE','VG1': 'Stoxx','NK1': 'Nikkei'})
# set Date to a datetime
df.Date = pd.to_datetime(df.Date)
# set Date as the index
df.set_index('Date', inplace=True)
# stack the dataframe
dfs = df.stack().reset_index().rename(columns={'level_1': 'Stock', 0: 'val'})
# to select only a subset of values from Stock, to plot, select them with Boolean indexing
df_select = dfs[dfs.Stock.isin(['Eminis', 'FTSE', 'Stoxx', 'Nikkei'])]`
# df_select.head()
Date Stock val
0 2005-01-04 Eminis -0.0126
1 2005-01-04 FTSE 0.0077
2 2005-01-04 Stoxx -0.0030
3 2005-01-04 Nikkei 0.0052
4 2005-01-05 Eminis -0.0065
# plot
sns.relplot(data=df_select, x='Date', y='val', col='Stock', col_wrap=2, kind='line')
What am I doing wrong here?
- The current implementation is inefficient, has a number of incorrect method calls, and undefined variables.
Dateis not defined forx = Datey2 = Notes:Notesis not defined.lineis not apltmethod and causes anAttributeError; it should beplt.ploty1 - y4are DataFrames, but passed to the plot method for the y-axis, which causesTypeError: unhashable type: 'numpy.ndarray'; one column should be passes asy..legendsis not a method; it's.legend- The legend must be shown for each subplot, if one is desired.
Eminis = df[['Date','Eminis']]
FTSE = df[['Date','FTSE']]
Stoxx = df[['Date','Stoxx']]
Nikkei = df[['Date','Nikkei']]
# create multiple plots via plt.subplots(rows,columns)
fig, axes = plt.subplots(2,2, figsize=(20,15))
x = df.Date
y1 = Eminis.Eminis
y2 = FTSE.FTSE
y3 = Stoxx.Stoxx
y4 = Nikkei.Nikkei
# one plot on each subplot
axes[0][0].plot(x,y1, label='Eminis')
axes[0][0].legend()
axes[0][1].plot(x,y2, label='FTSE')
axes[0][1].legend()
axes[1][0].plot(x,y3, label='Stoxx')
axes[1][0].legend()
axes[1][1].plot(x,y4, label='Nikkei')
axes[1][1].legend()
plt.show()
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