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Data processing error solved by a copy paste?
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I am encountering a very strange problem while processing data under Linux 16.04 using python 2.7.
I create a .csv file using this function :
from ast import literal_eval
with open('logs.csv') as f:
data = [literal_eval(line) for line in f]
the file is properly created and looks like that:
('2017-04-01 12:05:00','0.01770001','0.0177887','0.01780275','0.01770001')
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
('2017-04-01 12:15:00','0.01773','0.01780092','0.01780092','0.01773')
('2017-04-01 12:20:00','0.0178','0.01781212','0.01784922','0.01774015')
('2017-04-01 12:25:00','0.01781212','0.01774528','0.01782994','0.01774528')
('2017-04-01 12:30:00','0.01774529','0.0178732','0.01788145','0.01774509')
('2017-04-01 12:35:00','0.01788145','0.01793318','0.01793318','0.01788145')
('2017-04-01 12:40:00','0.01794','0.01780093','0.01799984','0.01780092')
('2017-04-01 12:45:00','0.01785694','0.01806699','0.01807519','0.01785694')
('2017-04-01 12:50:00','0.01807999','0.01819687','0.01827573','0.018027')
('2017-04-01 12:55:00','0.01819687','0.01825402','0.0184','0.01800011')
('2017-04-01 13:00:00','0.01822416','0.01830994','0.01835554','0.0181777')
('2017-04-01 13:05:00','0.01825415','0.01810171','0.01830986','0.01810008')
('2017-04-01 13:10:00','0.01810174','0.01818991','0.01818991','0.01810173')
('2017-04-01 13:15:00','0.01818991','0.01818002','0.01819687','0.01818001')
('2017-04-01 13:20:00','0.01818002','0.01821999','0.01822','0.01818001')
I then pass it throught this code to draw a graph :
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import dates, ticker
import matplotlib as mpl
from mpl_finance import candlestick_ohlc
from ast import literal_eval
mpl.style.use('default')
data =
ohlc_data =
with open('logsXMR.csv') as f:
data = [literal_eval(line) for line in f]
for line in data:
#ohlc_data.append((np.float64(line[0]), np.float64(line[1]), np.float64(line[2]), np.float64(line[3]), np.float64(line[4])))
ohlc_data.append((dates.datestr2num(line[0]), np.float64(line[1]), np.float64(line[2]), np.float64(line[3]), np.float64(line[4])))
fig, ax1 = plt.subplots()
candlestick_ohlc(ax1, ohlc_data, width = 0.5/((24*60)/5), colorup = 'g', colordown = 'r', alpha = 0.8)
#ax1.xaxis.set_major_formatter(dates.DateFormatter('%d/%m/%Y %H:%M'))
ax1.xaxis.set_major_locator(ticker.MaxNLocator(10))
plt.xticks(rotation = 30)
plt.grid()
plt.xlabel('Date')
plt.ylabel('Price')
plt.title('Historical Data XMRUSD')
plt.tight_layout()
plt.show()
But each time I get that error:
Traceback (most recent call last):
File "CSVing.py", line 15, in <module>
data = [literal_eval(line) for line in f]
File "/usr/lib/python2.7/ast.py", line 49, in literal_eval
node_or_string = parse(node_or_string, mode='eval')
File "/usr/lib/python2.7/ast.py", line 37, in parse
return compile(source, filename, mode, PyCF_ONLY_AST)
File "<unknown>", line 2
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
^
I don't understand why I get this error because if I simply copy and paste my datas into another file, everything works fine, I can draw my graph flawlessly. I just don't get it because the 2 data files are identicals, no added space or anything.
what can cause this error and how can I proceed to be able to used my generated data file directly without the need to copy paste the datas in another file ?
thanks in advance,
Pixelle
python csv matplotlib graph
asked Nov 19 at 11:27
Pixelle
102
add a comment |
up vote
1
down vote
favorite
I am encountering a very strange problem while processing data under Linux 16.04 using python 2.7.
I create a .csv file using this function :
from ast import literal_eval
with open('logs.csv') as f:
data = [literal_eval(line) for line in f]
the file is properly created and looks like that:
('2017-04-01 12:05:00','0.01770001','0.0177887','0.01780275','0.01770001')
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
('2017-04-01 12:15:00','0.01773','0.01780092','0.01780092','0.01773')
('2017-04-01 12:20:00','0.0178','0.01781212','0.01784922','0.01774015')
('2017-04-01 12:25:00','0.01781212','0.01774528','0.01782994','0.01774528')
('2017-04-01 12:30:00','0.01774529','0.0178732','0.01788145','0.01774509')
('2017-04-01 12:35:00','0.01788145','0.01793318','0.01793318','0.01788145')
('2017-04-01 12:40:00','0.01794','0.01780093','0.01799984','0.01780092')
('2017-04-01 12:45:00','0.01785694','0.01806699','0.01807519','0.01785694')
('2017-04-01 12:50:00','0.01807999','0.01819687','0.01827573','0.018027')
('2017-04-01 12:55:00','0.01819687','0.01825402','0.0184','0.01800011')
('2017-04-01 13:00:00','0.01822416','0.01830994','0.01835554','0.0181777')
('2017-04-01 13:05:00','0.01825415','0.01810171','0.01830986','0.01810008')
('2017-04-01 13:10:00','0.01810174','0.01818991','0.01818991','0.01810173')
('2017-04-01 13:15:00','0.01818991','0.01818002','0.01819687','0.01818001')
('2017-04-01 13:20:00','0.01818002','0.01821999','0.01822','0.01818001')
I then pass it throught this code to draw a graph :
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import dates, ticker
import matplotlib as mpl
from mpl_finance import candlestick_ohlc
from ast import literal_eval
mpl.style.use('default')
data =
ohlc_data =
with open('logsXMR.csv') as f:
data = [literal_eval(line) for line in f]
for line in data:
#ohlc_data.append((np.float64(line[0]), np.float64(line[1]), np.float64(line[2]), np.float64(line[3]), np.float64(line[4])))
ohlc_data.append((dates.datestr2num(line[0]), np.float64(line[1]), np.float64(line[2]), np.float64(line[3]), np.float64(line[4])))
fig, ax1 = plt.subplots()
candlestick_ohlc(ax1, ohlc_data, width = 0.5/((24*60)/5), colorup = 'g', colordown = 'r', alpha = 0.8)
#ax1.xaxis.set_major_formatter(dates.DateFormatter('%d/%m/%Y %H:%M'))
ax1.xaxis.set_major_locator(ticker.MaxNLocator(10))
plt.xticks(rotation = 30)
plt.grid()
plt.xlabel('Date')
plt.ylabel('Price')
plt.title('Historical Data XMRUSD')
plt.tight_layout()
plt.show()
But each time I get that error:
Traceback (most recent call last):
File "CSVing.py", line 15, in <module>
data = [literal_eval(line) for line in f]
File "/usr/lib/python2.7/ast.py", line 49, in literal_eval
node_or_string = parse(node_or_string, mode='eval')
File "/usr/lib/python2.7/ast.py", line 37, in parse
return compile(source, filename, mode, PyCF_ONLY_AST)
File "<unknown>", line 2
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
^
I don't understand why I get this error because if I simply copy and paste my datas into another file, everything works fine, I can draw my graph flawlessly. I just don't get it because the 2 data files are identicals, no added space or anything.
what can cause this error and how can I proceed to be able to used my generated data file directly without the need to copy paste the datas in another file ?
thanks in advance,
Pixelle
python csv matplotlib graph
asked Nov 19 at 11:27
Pixelle
102
Can you motivate why you useliteral_evalto create a text file? Useful ways to do such things arecsvorpandas.
– ImportanceOfBeingErnest
Nov 19 at 11:51
yes sure, it was the subject of my previous post, it was easier that way: stackoverflow.com/questions/52976469/…
– Pixelle
Nov 19 at 12:03
You didn't answer this comment though.
– ImportanceOfBeingErnest
Nov 19 at 12:05
you're are right, I guess I'm not quite familiar with Stack Overflow yet. I do have controle over the whole code but the graph part came from an example found on the internet so since it was working fine, I kept the code as it was and adapted my datas format.
– Pixelle
Nov 19 at 12:47
add a comment |
up vote
1
down vote
favorite
up vote
1
down vote
favorite
I am encountering a very strange problem while processing data under Linux 16.04 using python 2.7.
I create a .csv file using this function :
from ast import literal_eval
with open('logs.csv') as f:
data = [literal_eval(line) for line in f]
the file is properly created and looks like that:
('2017-04-01 12:05:00','0.01770001','0.0177887','0.01780275','0.01770001')
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
('2017-04-01 12:15:00','0.01773','0.01780092','0.01780092','0.01773')
('2017-04-01 12:20:00','0.0178','0.01781212','0.01784922','0.01774015')
('2017-04-01 12:25:00','0.01781212','0.01774528','0.01782994','0.01774528')
('2017-04-01 12:30:00','0.01774529','0.0178732','0.01788145','0.01774509')
('2017-04-01 12:35:00','0.01788145','0.01793318','0.01793318','0.01788145')
('2017-04-01 12:40:00','0.01794','0.01780093','0.01799984','0.01780092')
('2017-04-01 12:45:00','0.01785694','0.01806699','0.01807519','0.01785694')
('2017-04-01 12:50:00','0.01807999','0.01819687','0.01827573','0.018027')
('2017-04-01 12:55:00','0.01819687','0.01825402','0.0184','0.01800011')
('2017-04-01 13:00:00','0.01822416','0.01830994','0.01835554','0.0181777')
('2017-04-01 13:05:00','0.01825415','0.01810171','0.01830986','0.01810008')
('2017-04-01 13:10:00','0.01810174','0.01818991','0.01818991','0.01810173')
('2017-04-01 13:15:00','0.01818991','0.01818002','0.01819687','0.01818001')
('2017-04-01 13:20:00','0.01818002','0.01821999','0.01822','0.01818001')
I then pass it throught this code to draw a graph :
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import dates, ticker
import matplotlib as mpl
from mpl_finance import candlestick_ohlc
from ast import literal_eval
mpl.style.use('default')
data =
ohlc_data =
with open('logsXMR.csv') as f:
data = [literal_eval(line) for line in f]
for line in data:
#ohlc_data.append((np.float64(line[0]), np.float64(line[1]), np.float64(line[2]), np.float64(line[3]), np.float64(line[4])))
ohlc_data.append((dates.datestr2num(line[0]), np.float64(line[1]), np.float64(line[2]), np.float64(line[3]), np.float64(line[4])))
fig, ax1 = plt.subplots()
candlestick_ohlc(ax1, ohlc_data, width = 0.5/((24*60)/5), colorup = 'g', colordown = 'r', alpha = 0.8)
#ax1.xaxis.set_major_formatter(dates.DateFormatter('%d/%m/%Y %H:%M'))
ax1.xaxis.set_major_locator(ticker.MaxNLocator(10))
plt.xticks(rotation = 30)
plt.grid()
plt.xlabel('Date')
plt.ylabel('Price')
plt.title('Historical Data XMRUSD')
plt.tight_layout()
plt.show()
But each time I get that error:
Traceback (most recent call last):
File "CSVing.py", line 15, in <module>
data = [literal_eval(line) for line in f]
File "/usr/lib/python2.7/ast.py", line 49, in literal_eval
node_or_string = parse(node_or_string, mode='eval')
File "/usr/lib/python2.7/ast.py", line 37, in parse
return compile(source, filename, mode, PyCF_ONLY_AST)
File "<unknown>", line 2
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
^
I don't understand why I get this error because if I simply copy and paste my datas into another file, everything works fine, I can draw my graph flawlessly. I just don't get it because the 2 data files are identicals, no added space or anything.
what can cause this error and how can I proceed to be able to used my generated data file directly without the need to copy paste the datas in another file ?
thanks in advance,
Pixelle
python csv matplotlib graph
asked Nov 19 at 11:27
Pixelle
102
I am encountering a very strange problem while processing data under Linux 16.04 using python 2.7.
I create a .csv file using this function :
from ast import literal_eval
with open('logs.csv') as f:
data = [literal_eval(line) for line in f]
the file is properly created and looks like that:
('2017-04-01 12:05:00','0.01770001','0.0177887','0.01780275','0.01770001')
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
('2017-04-01 12:15:00','0.01773','0.01780092','0.01780092','0.01773')
('2017-04-01 12:20:00','0.0178','0.01781212','0.01784922','0.01774015')
('2017-04-01 12:25:00','0.01781212','0.01774528','0.01782994','0.01774528')
('2017-04-01 12:30:00','0.01774529','0.0178732','0.01788145','0.01774509')
('2017-04-01 12:35:00','0.01788145','0.01793318','0.01793318','0.01788145')
('2017-04-01 12:40:00','0.01794','0.01780093','0.01799984','0.01780092')
('2017-04-01 12:45:00','0.01785694','0.01806699','0.01807519','0.01785694')
('2017-04-01 12:50:00','0.01807999','0.01819687','0.01827573','0.018027')
('2017-04-01 12:55:00','0.01819687','0.01825402','0.0184','0.01800011')
('2017-04-01 13:00:00','0.01822416','0.01830994','0.01835554','0.0181777')
('2017-04-01 13:05:00','0.01825415','0.01810171','0.01830986','0.01810008')
('2017-04-01 13:10:00','0.01810174','0.01818991','0.01818991','0.01810173')
('2017-04-01 13:15:00','0.01818991','0.01818002','0.01819687','0.01818001')
('2017-04-01 13:20:00','0.01818002','0.01821999','0.01822','0.01818001')
I then pass it throught this code to draw a graph :
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import dates, ticker
import matplotlib as mpl
from mpl_finance import candlestick_ohlc
from ast import literal_eval
mpl.style.use('default')
data =
ohlc_data =
with open('logsXMR.csv') as f:
data = [literal_eval(line) for line in f]
for line in data:
#ohlc_data.append((np.float64(line[0]), np.float64(line[1]), np.float64(line[2]), np.float64(line[3]), np.float64(line[4])))
ohlc_data.append((dates.datestr2num(line[0]), np.float64(line[1]), np.float64(line[2]), np.float64(line[3]), np.float64(line[4])))
fig, ax1 = plt.subplots()
candlestick_ohlc(ax1, ohlc_data, width = 0.5/((24*60)/5), colorup = 'g', colordown = 'r', alpha = 0.8)
#ax1.xaxis.set_major_formatter(dates.DateFormatter('%d/%m/%Y %H:%M'))
ax1.xaxis.set_major_locator(ticker.MaxNLocator(10))
plt.xticks(rotation = 30)
plt.grid()
plt.xlabel('Date')
plt.ylabel('Price')
plt.title('Historical Data XMRUSD')
plt.tight_layout()
plt.show()
But each time I get that error:
Traceback (most recent call last):
File "CSVing.py", line 15, in <module>
data = [literal_eval(line) for line in f]
File "/usr/lib/python2.7/ast.py", line 49, in literal_eval
node_or_string = parse(node_or_string, mode='eval')
File "/usr/lib/python2.7/ast.py", line 37, in parse
return compile(source, filename, mode, PyCF_ONLY_AST)
File "<unknown>", line 2
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
^
I don't understand why I get this error because if I simply copy and paste my datas into another file, everything works fine, I can draw my graph flawlessly. I just don't get it because the 2 data files are identicals, no added space or anything.
what can cause this error and how can I proceed to be able to used my generated data file directly without the need to copy paste the datas in another file ?
thanks in advance,
Pixelle
python csv matplotlib graph
python csv matplotlib graph
asked Nov 19 at 11:27
Pixelle
102
asked Nov 19 at 11:27
Pixelle
102
asked Nov 19 at 11:27
Pixelle
102
asked Nov 19 at 11:27
Pixelle
102
asked Nov 19 at 11:27
Pixelle
102
102
Can you motivate why you useliteral_evalto create a text file? Useful ways to do such things arecsvorpandas.
– ImportanceOfBeingErnest
Nov 19 at 11:51
yes sure, it was the subject of my previous post, it was easier that way: stackoverflow.com/questions/52976469/…
– Pixelle
Nov 19 at 12:03
You didn't answer this comment though.
– ImportanceOfBeingErnest
Nov 19 at 12:05
you're are right, I guess I'm not quite familiar with Stack Overflow yet. I do have controle over the whole code but the graph part came from an example found on the internet so since it was working fine, I kept the code as it was and adapted my datas format.
– Pixelle
Nov 19 at 12:47
add a comment |
Can you motivate why you useliteral_evalto create a text file? Useful ways to do such things arecsvorpandas.
– ImportanceOfBeingErnest
Nov 19 at 11:51
yes sure, it was the subject of my previous post, it was easier that way: stackoverflow.com/questions/52976469/…
– Pixelle
Nov 19 at 12:03
You didn't answer this comment though.
– ImportanceOfBeingErnest
Nov 19 at 12:05
you're are right, I guess I'm not quite familiar with Stack Overflow yet. I do have controle over the whole code but the graph part came from an example found on the internet so since it was working fine, I kept the code as it was and adapted my datas format.
– Pixelle
Nov 19 at 12:47
Can you motivate why you use
literal_eval to create a text file? Useful ways to do such things are csv or pandas.– ImportanceOfBeingErnest
Nov 19 at 11:51
Can you motivate why you use
literal_eval to create a text file? Useful ways to do such things are csv or pandas.– ImportanceOfBeingErnest
Nov 19 at 11:51
yes sure, it was the subject of my previous post, it was easier that way: stackoverflow.com/questions/52976469/…
– Pixelle
Nov 19 at 12:03
yes sure, it was the subject of my previous post, it was easier that way: stackoverflow.com/questions/52976469/…
– Pixelle
Nov 19 at 12:03
You didn't answer this comment though.
– ImportanceOfBeingErnest
Nov 19 at 12:05
You didn't answer this comment though.
– ImportanceOfBeingErnest
Nov 19 at 12:05
you're are right, I guess I'm not quite familiar with Stack Overflow yet. I do have controle over the whole code but the graph part came from an example found on the internet so since it was working fine, I kept the code as it was and adapted my datas format.
– Pixelle
Nov 19 at 12:47
you're are right, I guess I'm not quite familiar with Stack Overflow yet. I do have controle over the whole code but the graph part came from an example found on the internet so since it was working fine, I kept the code as it was and adapted my datas format.
– Pixelle
Nov 19 at 12:47
add a comment |
1 Answer
1
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0
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I would recommend rethinking the data format you have. I don't know where the data comes from, but it would be reasonable to store it in a way that does not contain parantheses etc.
If you really need to work with this data format, you may still use e.g. pandas and sanitize the format, by removing the characters that aren't useful.
u = """('2017-04-01 12:05:00','0.01770001','0.0177887','0.01780275','0.01770001')
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
('2017-04-01 12:15:00','0.01773','0.01780092','0.01780092','0.01773')
('2017-04-01 12:20:00','0.0178','0.01781212','0.01784922','0.01774015')
('2017-04-01 12:25:00','0.01781212','0.01774528','0.01782994','0.01774528')
('2017-04-01 12:30:00','0.01774529','0.0178732','0.01788145','0.01774509')
('2017-04-01 12:35:00','0.01788145','0.01793318','0.01793318','0.01788145')
('2017-04-01 12:40:00','0.01794','0.01780093','0.01799984','0.01780092')
('2017-04-01 12:45:00','0.01785694','0.01806699','0.01807519','0.01785694')
('2017-04-01 12:50:00','0.01807999','0.01819687','0.01827573','0.018027')
('2017-04-01 12:55:00','0.01819687','0.01825402','0.0184','0.01800011')
('2017-04-01 13:00:00','0.01822416','0.01830994','0.01835554','0.0181777')
('2017-04-01 13:05:00','0.01825415','0.01810171','0.01830986','0.01810008')
('2017-04-01 13:10:00','0.01810174','0.01818991','0.01818991','0.01810173')
('2017-04-01 13:15:00','0.01818991','0.01818002','0.01819687','0.01818001')
('2017-04-01 13:20:00','0.01818002','0.01821999','0.01822','0.01818001')"""
import io
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import dates
from mpl_finance import candlestick_ohlc
replace = {"(" : "", ")" : "", "'" : ""}
df = pd.read_csv(io.StringIO(u), sep=",", header=None).replace(replace, regex=True)
# use pd.read_csv("myfilename.txt", ...) here for your real file
df[0] = dates.datestr2num(df[0])
df.iloc[:,1:] = df.iloc[:,1:].astype(float)
fig, ax1 = plt.subplots()
candlestick_ohlc(ax1, df.values, width = 0.5/((24*60)/5),
colorup = 'g', colordown = 'r', alpha = 0.8)
ax1.xaxis.set_major_formatter(dates.DateFormatter('%d/%m/%Y %H:%M'))
ax1.xaxis.set_major_locator(dates.MinuteLocator((0,15,30,45)))
plt.xticks(rotation = 30)
plt.grid()
plt.xlabel('Date')
plt.ylabel('Price')
plt.title('Historical Data XMRUSD')
plt.tight_layout()
plt.show()
Note that the data also does not seem to be in Ohlc format, hence the strange looking graph. But since nothing is known about the data, you need to find out the correct order yourself.
answered Nov 19 at 12:51
ImportanceOfBeingErnest
119k10116189
You were right, I integrated that into my main code and it work like a charm. thank you ! I should have used a more standard way of doing things from the beginning.
– Pixelle
Nov 19 at 13:38
add a comment |
1 Answer
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I would recommend rethinking the data format you have. I don't know where the data comes from, but it would be reasonable to store it in a way that does not contain parantheses etc.
If you really need to work with this data format, you may still use e.g. pandas and sanitize the format, by removing the characters that aren't useful.
u = """('2017-04-01 12:05:00','0.01770001','0.0177887','0.01780275','0.01770001')
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
('2017-04-01 12:15:00','0.01773','0.01780092','0.01780092','0.01773')
('2017-04-01 12:20:00','0.0178','0.01781212','0.01784922','0.01774015')
('2017-04-01 12:25:00','0.01781212','0.01774528','0.01782994','0.01774528')
('2017-04-01 12:30:00','0.01774529','0.0178732','0.01788145','0.01774509')
('2017-04-01 12:35:00','0.01788145','0.01793318','0.01793318','0.01788145')
('2017-04-01 12:40:00','0.01794','0.01780093','0.01799984','0.01780092')
('2017-04-01 12:45:00','0.01785694','0.01806699','0.01807519','0.01785694')
('2017-04-01 12:50:00','0.01807999','0.01819687','0.01827573','0.018027')
('2017-04-01 12:55:00','0.01819687','0.01825402','0.0184','0.01800011')
('2017-04-01 13:00:00','0.01822416','0.01830994','0.01835554','0.0181777')
('2017-04-01 13:05:00','0.01825415','0.01810171','0.01830986','0.01810008')
('2017-04-01 13:10:00','0.01810174','0.01818991','0.01818991','0.01810173')
('2017-04-01 13:15:00','0.01818991','0.01818002','0.01819687','0.01818001')
('2017-04-01 13:20:00','0.01818002','0.01821999','0.01822','0.01818001')"""
import io
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import dates
from mpl_finance import candlestick_ohlc
replace = {"(" : "", ")" : "", "'" : ""}
df = pd.read_csv(io.StringIO(u), sep=",", header=None).replace(replace, regex=True)
# use pd.read_csv("myfilename.txt", ...) here for your real file
df[0] = dates.datestr2num(df[0])
df.iloc[:,1:] = df.iloc[:,1:].astype(float)
fig, ax1 = plt.subplots()
candlestick_ohlc(ax1, df.values, width = 0.5/((24*60)/5),
colorup = 'g', colordown = 'r', alpha = 0.8)
ax1.xaxis.set_major_formatter(dates.DateFormatter('%d/%m/%Y %H:%M'))
ax1.xaxis.set_major_locator(dates.MinuteLocator((0,15,30,45)))
plt.xticks(rotation = 30)
plt.grid()
plt.xlabel('Date')
plt.ylabel('Price')
plt.title('Historical Data XMRUSD')
plt.tight_layout()
plt.show()
Note that the data also does not seem to be in Ohlc format, hence the strange looking graph. But since nothing is known about the data, you need to find out the correct order yourself.
answered Nov 19 at 12:51
ImportanceOfBeingErnest
119k10116189
You were right, I integrated that into my main code and it work like a charm. thank you ! I should have used a more standard way of doing things from the beginning.
– Pixelle
Nov 19 at 13:38
add a comment |
up vote
0
down vote
accepted
I would recommend rethinking the data format you have. I don't know where the data comes from, but it would be reasonable to store it in a way that does not contain parantheses etc.
If you really need to work with this data format, you may still use e.g. pandas and sanitize the format, by removing the characters that aren't useful.
u = """('2017-04-01 12:05:00','0.01770001','0.0177887','0.01780275','0.01770001')
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
('2017-04-01 12:15:00','0.01773','0.01780092','0.01780092','0.01773')
('2017-04-01 12:20:00','0.0178','0.01781212','0.01784922','0.01774015')
('2017-04-01 12:25:00','0.01781212','0.01774528','0.01782994','0.01774528')
('2017-04-01 12:30:00','0.01774529','0.0178732','0.01788145','0.01774509')
('2017-04-01 12:35:00','0.01788145','0.01793318','0.01793318','0.01788145')
('2017-04-01 12:40:00','0.01794','0.01780093','0.01799984','0.01780092')
('2017-04-01 12:45:00','0.01785694','0.01806699','0.01807519','0.01785694')
('2017-04-01 12:50:00','0.01807999','0.01819687','0.01827573','0.018027')
('2017-04-01 12:55:00','0.01819687','0.01825402','0.0184','0.01800011')
('2017-04-01 13:00:00','0.01822416','0.01830994','0.01835554','0.0181777')
('2017-04-01 13:05:00','0.01825415','0.01810171','0.01830986','0.01810008')
('2017-04-01 13:10:00','0.01810174','0.01818991','0.01818991','0.01810173')
('2017-04-01 13:15:00','0.01818991','0.01818002','0.01819687','0.01818001')
('2017-04-01 13:20:00','0.01818002','0.01821999','0.01822','0.01818001')"""
import io
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import dates
from mpl_finance import candlestick_ohlc
replace = {"(" : "", ")" : "", "'" : ""}
df = pd.read_csv(io.StringIO(u), sep=",", header=None).replace(replace, regex=True)
# use pd.read_csv("myfilename.txt", ...) here for your real file
df[0] = dates.datestr2num(df[0])
df.iloc[:,1:] = df.iloc[:,1:].astype(float)
fig, ax1 = plt.subplots()
candlestick_ohlc(ax1, df.values, width = 0.5/((24*60)/5),
colorup = 'g', colordown = 'r', alpha = 0.8)
ax1.xaxis.set_major_formatter(dates.DateFormatter('%d/%m/%Y %H:%M'))
ax1.xaxis.set_major_locator(dates.MinuteLocator((0,15,30,45)))
plt.xticks(rotation = 30)
plt.grid()
plt.xlabel('Date')
plt.ylabel('Price')
plt.title('Historical Data XMRUSD')
plt.tight_layout()
plt.show()
Note that the data also does not seem to be in Ohlc format, hence the strange looking graph. But since nothing is known about the data, you need to find out the correct order yourself.
answered Nov 19 at 12:51
ImportanceOfBeingErnest
119k10116189
You were right, I integrated that into my main code and it work like a charm. thank you ! I should have used a more standard way of doing things from the beginning.
– Pixelle
Nov 19 at 13:38
add a comment |
up vote
0
down vote
accepted
up vote
0
down vote
accepted
I would recommend rethinking the data format you have. I don't know where the data comes from, but it would be reasonable to store it in a way that does not contain parantheses etc.
If you really need to work with this data format, you may still use e.g. pandas and sanitize the format, by removing the characters that aren't useful.
u = """('2017-04-01 12:05:00','0.01770001','0.0177887','0.01780275','0.01770001')
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
('2017-04-01 12:15:00','0.01773','0.01780092','0.01780092','0.01773')
('2017-04-01 12:20:00','0.0178','0.01781212','0.01784922','0.01774015')
('2017-04-01 12:25:00','0.01781212','0.01774528','0.01782994','0.01774528')
('2017-04-01 12:30:00','0.01774529','0.0178732','0.01788145','0.01774509')
('2017-04-01 12:35:00','0.01788145','0.01793318','0.01793318','0.01788145')
('2017-04-01 12:40:00','0.01794','0.01780093','0.01799984','0.01780092')
('2017-04-01 12:45:00','0.01785694','0.01806699','0.01807519','0.01785694')
('2017-04-01 12:50:00','0.01807999','0.01819687','0.01827573','0.018027')
('2017-04-01 12:55:00','0.01819687','0.01825402','0.0184','0.01800011')
('2017-04-01 13:00:00','0.01822416','0.01830994','0.01835554','0.0181777')
('2017-04-01 13:05:00','0.01825415','0.01810171','0.01830986','0.01810008')
('2017-04-01 13:10:00','0.01810174','0.01818991','0.01818991','0.01810173')
('2017-04-01 13:15:00','0.01818991','0.01818002','0.01819687','0.01818001')
('2017-04-01 13:20:00','0.01818002','0.01821999','0.01822','0.01818001')"""
import io
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import dates
from mpl_finance import candlestick_ohlc
replace = {"(" : "", ")" : "", "'" : ""}
df = pd.read_csv(io.StringIO(u), sep=",", header=None).replace(replace, regex=True)
# use pd.read_csv("myfilename.txt", ...) here for your real file
df[0] = dates.datestr2num(df[0])
df.iloc[:,1:] = df.iloc[:,1:].astype(float)
fig, ax1 = plt.subplots()
candlestick_ohlc(ax1, df.values, width = 0.5/((24*60)/5),
colorup = 'g', colordown = 'r', alpha = 0.8)
ax1.xaxis.set_major_formatter(dates.DateFormatter('%d/%m/%Y %H:%M'))
ax1.xaxis.set_major_locator(dates.MinuteLocator((0,15,30,45)))
plt.xticks(rotation = 30)
plt.grid()
plt.xlabel('Date')
plt.ylabel('Price')
plt.title('Historical Data XMRUSD')
plt.tight_layout()
plt.show()
Note that the data also does not seem to be in Ohlc format, hence the strange looking graph. But since nothing is known about the data, you need to find out the correct order yourself.
answered Nov 19 at 12:51
ImportanceOfBeingErnest
119k10116189
I would recommend rethinking the data format you have. I don't know where the data comes from, but it would be reasonable to store it in a way that does not contain parantheses etc.
If you really need to work with this data format, you may still use e.g. pandas and sanitize the format, by removing the characters that aren't useful.
u = """('2017-04-01 12:05:00','0.01770001','0.0177887','0.01780275','0.01770001')
('2017-04-01 12:10:00','0.0177887','0.01771308','0.01785263','0.01771039')
('2017-04-01 12:15:00','0.01773','0.01780092','0.01780092','0.01773')
('2017-04-01 12:20:00','0.0178','0.01781212','0.01784922','0.01774015')
('2017-04-01 12:25:00','0.01781212','0.01774528','0.01782994','0.01774528')
('2017-04-01 12:30:00','0.01774529','0.0178732','0.01788145','0.01774509')
('2017-04-01 12:35:00','0.01788145','0.01793318','0.01793318','0.01788145')
('2017-04-01 12:40:00','0.01794','0.01780093','0.01799984','0.01780092')
('2017-04-01 12:45:00','0.01785694','0.01806699','0.01807519','0.01785694')
('2017-04-01 12:50:00','0.01807999','0.01819687','0.01827573','0.018027')
('2017-04-01 12:55:00','0.01819687','0.01825402','0.0184','0.01800011')
('2017-04-01 13:00:00','0.01822416','0.01830994','0.01835554','0.0181777')
('2017-04-01 13:05:00','0.01825415','0.01810171','0.01830986','0.01810008')
('2017-04-01 13:10:00','0.01810174','0.01818991','0.01818991','0.01810173')
('2017-04-01 13:15:00','0.01818991','0.01818002','0.01819687','0.01818001')
('2017-04-01 13:20:00','0.01818002','0.01821999','0.01822','0.01818001')"""
import io
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import dates
from mpl_finance import candlestick_ohlc
replace = {"(" : "", ")" : "", "'" : ""}
df = pd.read_csv(io.StringIO(u), sep=",", header=None).replace(replace, regex=True)
# use pd.read_csv("myfilename.txt", ...) here for your real file
df[0] = dates.datestr2num(df[0])
df.iloc[:,1:] = df.iloc[:,1:].astype(float)
fig, ax1 = plt.subplots()
candlestick_ohlc(ax1, df.values, width = 0.5/((24*60)/5),
colorup = 'g', colordown = 'r', alpha = 0.8)
ax1.xaxis.set_major_formatter(dates.DateFormatter('%d/%m/%Y %H:%M'))
ax1.xaxis.set_major_locator(dates.MinuteLocator((0,15,30,45)))
plt.xticks(rotation = 30)
plt.grid()
plt.xlabel('Date')
plt.ylabel('Price')
plt.title('Historical Data XMRUSD')
plt.tight_layout()
plt.show()
Note that the data also does not seem to be in Ohlc format, hence the strange looking graph. But since nothing is known about the data, you need to find out the correct order yourself.
answered Nov 19 at 12:51
ImportanceOfBeingErnest
119k10116189
answered Nov 19 at 12:51
ImportanceOfBeingErnest
119k10116189
answered Nov 19 at 12:51
ImportanceOfBeingErnest
119k10116189
answered Nov 19 at 12:51
ImportanceOfBeingErnest
119k10116189
119k10116189
You were right, I integrated that into my main code and it work like a charm. thank you ! I should have used a more standard way of doing things from the beginning.
– Pixelle
Nov 19 at 13:38
add a comment |
You were right, I integrated that into my main code and it work like a charm. thank you ! I should have used a more standard way of doing things from the beginning.
– Pixelle
Nov 19 at 13:38
You were right, I integrated that into my main code and it work like a charm. thank you ! I should have used a more standard way of doing things from the beginning.
– Pixelle
Nov 19 at 13:38
You were right, I integrated that into my main code and it work like a charm. thank you ! I should have used a more standard way of doing things from the beginning.
– Pixelle
Nov 19 at 13:38
add a comment |
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Can you motivate why you use
literal_evalto create a text file? Useful ways to do such things arecsvorpandas.– ImportanceOfBeingErnest
Nov 19 at 11:51
yes sure, it was the subject of my previous post, it was easier that way: stackoverflow.com/questions/52976469/…
– Pixelle
Nov 19 at 12:03
You didn't answer this comment though.
– ImportanceOfBeingErnest
Nov 19 at 12:05
you're are right, I guess I'm not quite familiar with Stack Overflow yet. I do have controle over the whole code but the graph part came from an example found on the internet so since it was working fine, I kept the code as it was and adapted my datas format.
– Pixelle
Nov 19 at 12:47