我查看了对原始问题的回答(see here,但似乎无法解决我的问题。)
var Cat = {
create: function(firstName, lastName, color){
var self = Object.create(this);
Object.defineProperty(self,'name', {configurable: false, value: {}});
self.name.first = firstName;
self.name.last = lastName;
Object.freeze(self.name);
Object.freeze(self.color);
return self;
},
name: {first: '', last: ''},
color: ''
}
var cat = Cat.create('frisky','smith','white');
console.log(cat.name);
该图显示很好,但我想不出一种仅显示特定日期范围的方法。我已经尝试了一切。
import pandas as pd
import pandas_datareader.data
import datetime
import matplotlib.pyplot as plt
df = pd.read_csv(mypath + filename, \
skiprows=4,index_col=0,usecols=['Day', 'Cushing OK Crude Oil Future Contract 1 Dollars per Barrel'], \
skipfooter=0,engine='python')
df.index = pd.to_datetime(df.index)
fig = plt.figure(figsize=plt.figaspect(0.25))
ax = fig.add_subplot(1,1,1)
ax.grid(axis='y',color='lightgrey', linestyle='--', linewidth=0.5)
ax.grid(axis='x',color='lightgrey', linestyle='none', linewidth=0.5)
df['Cushing OK Crude Oil Future Contract 1 Dollars per
Barrel'].plot(ax=ax,grid = True, \
color='blue',fontsize=14,legend=False)
plt.show()
此外,列type(df) = pandas.core.frame.DataFrame
type(df.index) = pandas.core.indexes.datetimes.DatetimeIndex
的格式为'Day'
答案 0 :(得分:0)
假设数据框上有一个日期时间索引(看起来像那样),则可以像这样使用.loc
进行切片:
% matplotlib inline
import pandas as pd
import numpy as np
data = pd.DataFrame({'values': np.random.rand(31)}, index = pd.date_range('2018-01-01', '2018-01-31'))
# Plot the entire dataframe.
data.plot()
# Plot a slice of the dataframe.
data.loc['2018-01-05':'2018-01-10', 'values'].plot(legend = False)
礼物:
橙色系列是切片。