为什么非常相似的数据帧的熊猫图如此不同？
为什么非常相似的数据帧的熊猫图如此不同？
提问于 2018-02-02 03:45:50
以下代码片段在打印时部分显示，执行时没有任何问题：
import pandas as pd
from matplotlib import pyplot as plt
import numpy as np
import csv
ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))
df = pd.DataFrame(np.random.randn(1000, 3), index=ts.index, columns=list('ABC'))
print (df)
print (df.index)
print (df.columns)
#df = df.cumsum() # this also is ok
df.plot()
plt.show()
A B C
2000-01-01 0.882544 -0.841398 1.745238
2000-01-02 1.798310 1.049662 -0.115292
2000-01-03 1.223243 -0.086322 -0.565204
2000-01-04 -0.587905 -0.609485 0.296248
2000-01-05 -1.603916 -0.397210 0.007550
2000-01-06 -0.821833 0.112760 -0.082558
...
...
2002-09-22 -0.530537 0.373358 2.920919
2002-09-23 0.121657 0.634864 -0.964255
2002-09-24 1.153799 2.468507 -2.087136
2002-09-25 -1.079853 0.684926 1.556522
2002-09-26 -2.163454 0.874373 1.942925
[1000 rows x 3 columns]
DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-03', '2000-01-04',
'2000-01-05', '2000-01-06', '2000-01-07', '2000-01-08',
'2000-01-09', '2000-01-10',
...
...
'2002-09-17', '2002-09-18', '2002-09-19', '2002-09-20',
'2002-09-21', '2002-09-22', '2002-09-23', '2002-09-24',
'2002-09-25', '2002-09-26'],
dtype='datetime64[ns]', length=1000, freq='D')
Index(['A', 'B', 'C'], dtype='object')并生成一个很好的图(正如预期的那样)
但是，当我执行以下代码时
import datetime
df = pd.read_csv(fullFileNameOutCSV, header=0, names=headerCSV,usecols=['SEK/EUR', 'SEK/DKK', 'SEK/NOK'])
pd.Timedelta(datetime.timedelta(days=1))
df.index = pd.date_range('2000-01-01',periods=4888)
df.index = pd.to_datetime(df.index)
print (df)
print (df.index)
print (df.columns)
df.plot()
plt.show()
SEK/EUR SEK/DKK SEK/NOK
2000-01-01 9.4696 7.4501 8.8550
2000-01-02 9.4025 7.4495 8.7745
2000-01-03 9.3050 7.4452 8.7335
2000-01-04 9.1800 7.4431 8.6295
2000-01-05 9.1650 7.4433 8.5900
2000-01-06 9.0985 7.4433 8.5585
...
...
2013-05-14 9.8188 7.4444 9.5858
2013-05-15 9.8005 7.4428 9.5655
2013-05-16 9.7823 7.4427 9.5548
2013-05-17 9.7825 7.4415 9.5628
2013-05-18 9.7645 7.4419 9.5620
2013-05-19 9.8030 7.4428 9.5705
[4888 rows x 3 columns]
DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-03', '2000-01-04',
'2000-01-05', '2000-01-06', '2000-01-07', '2000-01-08',
'2000-01-09', '2000-01-10',
...
...
'2013-05-10', '2013-05-11', '2013-05-12', '2013-05-13',
'2013-05-14', '2013-05-15', '2013-05-16', '2013-05-17',
'2013-05-18', '2013-05-19'],
dtype='datetime64[ns]', length=4888, freq='D')剧情并不是我所期望的。
我在这段代码上尝试了许多不同的变体，以获得合理的绘图，但到目前为止，我还没有找到能够生成与第一个绘图类似的绘图的代码。请注意，垂直轴比例-是什么导致的？为什么我得不到与第一个代码片段类似的图？
回答 3
Stack Overflow用户
发布于 2018-02-02 08:28:04
在修改字符串以输出到csv文件的位置插入了以下代码，该代码工作正常- Eureka :-)
if '.' not in nums[3]:
# Append '.00' to integer strings
nums[3] = nums[3] + '.00' Stack Overflow用户
发布于 2018-02-02 09:04:02
以下是修改代码后的校正后的图
Stack Overflow用户
发布于 2018-02-03 04:28:25
我使用下面的函数来计算每种货币的均值和方差。如果我一直在使用，这3个异常值很容易就会被注意到-我现在就是。
def updateMeanVar(x,k,mu,vr):
'''
Purpose: Update the estimates for the mean and variance
(recursive algorithm)
Inputs:
x -- new value (x_k) x_1,x_2,...
k -- counter (index) for new value 1,2,
mu -- previously estimated mean (x_k not included)
vr -- previously estimated variance (x_k not included)
Otputs:
mu -- updated mean (with x_k included)
vr -- updated variance (with x_k included)
Refs.
Donald E. Knuth. Seminumerical Algorithms, volume 2 of The Art of Computer Programming,
chapter 4.2.2, page 232. Addison-Wesley, Boston, third edition, 1998.
'''
delta = x - mu
mu += delta/k
vr += delta*(x - mu)
return mu,vr以下是欧洲中央银行(ECB)货币汇率的部分输出，包括今天的估计。
Processing ECB exchange rates ...
Saving data ...
ECB working days: 4889
strt date: 1999-01-04
stop date: 2018-02-02
Exchange rates stored in:
Sweden (SEK/EUR): E:/Data/ECB_ExchangeRates/Sweden/Rates.txt (mean= 9.235,std= 0.496)
Denmark (DKK/EUR): E:/Data/ECB_ExchangeRates/Denmark/Rates.txt (mean= 7.448,std= 0.011)
Norway (NOK/EUR): E:/Data/ECB_ExchangeRates/Norway/Rates.txt (mean= 8.238,std= 0.565)
All rates stored in: E:/Data/ECB_ExchangeRates/AllRates.txt
E:/Data/ECB_ExchangeRates/AllRates.csv和摘要图。
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/48570596
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