Here is the result. As you can see the order is 1,2,4,3 it should be 1,2,3,4. Here how i render it
import csv
import matplotlib.pyplot as plt
time = []
total = []
with open('new.csv','r') as csvfile:
plots = csv.reader(csvfile, delimiter = ',')
for row in plots:
time.append(row[0])
total.append(row[1])
plt.plot(time, total)
plt.xlabel('Dates')
plt.ylabel('Transactions')
plt.show()
and here is my csv
2022-08-25,1
2022-08-26,2
2022-08-27,4
2022-08-29,3
How can i fix it ? thanks in advance
The problem with your code is that the y-values are strings. This simple casting to float would fix that:
import matplotlib.pyplot as plt
import csv
time = []
total = []
with open('new.csv','r') as csvfile:
plots = csv.reader(csvfile, delimiter = ',')
for row in plots:
time.append(row[0])
total.append(float(row[1]))
plt.plot(time, total)
plt.xlabel('Dates')
plt.ylabel('Transactions')
plt.show()
But notice there is also the same problem with dates, last two dates are not one day from each other but twice as much. Matplotlib know how to handle datetimes though:
import csv
from datetime import datetime as dt
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
time = []
total = []
with open('new.csv','r') as csvfile:
plots = csv.reader(csvfile, delimiter = ',')
for row in plots:
time.append(dt.strptime(row[0], "%Y-%m-%d"))
total.append(float(row[1]))
plt.plot(time, total)
plt.xlabel('Dates')
plt.ylabel('Transactions')
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d %H:%M:%S'))
plt.gcf().autofmt_xdate()
plt.show()
Little help taken from: Format of datetime in pyplot axis
Related
How to convert str to date? I also want the date only appears mm/yy as the x-axis in the plot.
The data shows as below.
21/12/2020, 0,
22/12/2020, 1,
23/12/2020, 0,
24/12/2020, 0,
25/12/2020, 1,
Below is the code I used.
import numpy as np
import matplotlib.dates as mdates
from datetime import datetime as dt
import csv
with open('p211.csv', newline='') as f:
reader = csv.reader(f)
rain = []
for row in reader:
rain_t = float(row[1])
rain.append(rain_t)
import csv
with open('p211.csv', newline='') as f:
reader = csv.reader(f)
date = []
for row in reader:
date_t=str(row[0])
date.append(date_t)
P=np.array(rain)
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(20, 12))
ax.bar(x=date, height=P, color='royalblue')
ax.legend()
ax.set_ylabel('Inputs [mm/day]')
plt.show()
using datetime package
from datetime import datetime
datetime.strptime(dtime, '%d/%m/%Y') # dtime = '21/12/2020'
I basically want to convert the unix time values I have in the first row of my text file named 'EKTE9' to date. I think using the datetime library is the way to go, but I don't know how to implement that in my code. Some answers would be appreciated.
import matplotlib.pyplot as plt
import csv
x = []
y = []
with open('EKTE9.txt','r') as csvfile:
plots = csv.reader(csvfile, delimiter=',')
for row in plots:
x.append(int(row[0]))
y.append(float(row[3]))
plt.plot(x,y, label='Temperatur')
plt.xlabel('Tid')
plt.ylabel('Temperatur')
plt.title('Grafen viser temperatur under forsøket\n')
plt.legend()
plt.show()
Here are some values from the EKTE9.txt file:
1554058225,0.80,2.90,13.60,27.20
1554058525,0.30,0.80,9.60,26.70
The values goes on for about 200 lines
That did the job. Thank you very much Martin Evans.
Fina code:
import matplotlib
import matplotlib.pyplot as plt
from datetime import datetime
import csv
x = []
y = []
with open('EKTE9.txt','r') as csvfile:
plots = csv.reader(csvfile, delimiter=',')
for row in plots:
x.append(matplotlib.dates.date2num(datetime.fromtimestamp(int(row[0]))))
y.append(float(row[3]))
hfmt = matplotlib.dates.DateFormatter('%d\n%H:%M')
plt.plot(x,y, label='Temperatur')
plt.gca().xaxis.set_major_formatter(hfmt)
plt.xlabel('Tid')
plt.ylabel('Temperatur')
plt.title('Grafen viser temperatur under forsøket\n')
plt.legend()
plt.show()
You would first create a datetime object using datetime.fromtimestamp(). This can then be converted to a matplotlib number using date2num(). Finally, you should use a DateFormatter() to help with displaying the x-axis.
import matplotlib
import matplotlib.pyplot as plt
from datetime import datetime
import csv
x = []
y = []
with open('EKTE9.txt', 'r', newline='') as csvfile:
plots = csv.reader(csvfile, delimiter=',')
for row in plots:
x.append(matplotlib.dates.date2num(datetime.fromtimestamp(int(row[0]))))
y.append(float(row[3]))
hfmt = matplotlib.dates.DateFormatter('%d\n%H:%M')
plt.plot(x,y, label='Temperatur')
plt.gca().xaxis.set_major_formatter(hfmt)
plt.xlabel('Tid')
plt.ylabel('Temperatur')
plt.title('Grafen viser temperatur under forsøket\n')
plt.legend()
plt.show()
This would then show your two values as follows:
I am having a text file with time and a float value. I have heard that it is possible to plot these two columns using matplotlib. Searched similar threads but could not make it happening. My code and Data are-
import math
import datetime
import matplotlib
import matplotlib.pyplot as plt
import csv
with open('MaxMin.txt','r') as f_input:
csv_input = csv.reader(f_input, delimiter=' ', skipinitialspace=True)
x = []
y = []
for cols in csv_input:
x = matplotlib.dates.date2num(cols[0])
y = [float(cols[1])]
# naming the x axis
plt.xlabel('Real-Time')
# naming the y axis
plt.ylabel('Acceleration (m/s2)')
# giving a title to my graph
plt.title('Accelerometer reading graph!')
# plotting the points
plt.plot(x, y)
# beautify the x-labels
plt.gcf().autofmt_xdate()
# function to show the plot
plt.show()
And part of the Data in MaxMin.txt
23:28:30.137 10.7695982757
23:28:30.161 10.4071263594
23:28:30.187 9.23969855461
23:28:30.212 9.21066485657
23:28:30.238 9.25117645762
23:28:30.262 9.59227680741
23:28:30.287 9.9773536301
23:28:30.312 10.0128275058
23:28:30.337 9.73353441664
23:28:30.361 9.75064993988
23:28:30.387 9.717339267
23:28:30.412 9.72736788911
23:28:30.440 9.62451269364
I am a beginner in Python and on python 2.7.15 in windows 10 pro(64 bit). I have installed numpy,scipy scikit-learn already. Please help.
Final Output Graph from complete Data Set. Thanks # ImportanceOfBeingErnest
You could use pandas to achieve this, first store your file in a .csv format:
import math
import datetime
import matplotlib
import matplotlib.pyplot as plt
import pandas as pd #### import this library
df = pd.read_csv("path_to_file.csv", delimiter=' ', encoding='latin-1')
x = df.ix[:,0]
y = df.ix[:,1]
# naming the x axis
plt.xlabel('Real-Time')
# naming the y axis
plt.ylabel('Acceleration (m/s2)')
# giving a title to my graph
plt.title('Accelerometer reading graph!')
# plotting the points
plt.plot(x, y)
# beautify the x-labels
plt.gcf().autofmt_xdate()
# function to show the plot
plt.show()
if the first colunm does not have a datatime format you may convert it to this format like df.ix[:,0] = pd.to_datetime(df.ix[:,0])
and you take the hour for example:
df.ix[:,0] = df.ix[:,0].map(lambda x: x.hour)
The output after running the code was like:
The error you made in the original attempt is actually pretty minor. Instead of appending the values from the loop you redefined them.
Also you would need to use datestr2num instead of date2num, because the string read in is not yet a date.
import matplotlib
import matplotlib.pyplot as plt
import csv
with open('MaxMin.txt','r') as f_input:
csv_input = csv.reader(f_input, delimiter=' ', skipinitialspace=True)
x = []
y = []
for cols in csv_input:
x.append(matplotlib.dates.datestr2num(cols[0]))
y.append(float(cols[1]))
# naming the x axis
plt.xlabel('Real-Time')
# naming the y axis
plt.ylabel('Acceleration (m/s2)')
# giving a title to my graph
plt.title('Accelerometer reading graph!')
# plotting the points
plt.plot_date(x, y)
# beautify the x-labels
plt.gcf().autofmt_xdate()
# function to show the plot
plt.show()
My recommendation for how to make this easier would be, to use numpy and convert the input to datetime.
from datetime import datetime
import numpy as np
import matplotlib.pyplot as plt
x,y= np.loadtxt('MaxMin.txt', dtype=str, unpack=True)
x = np.array([datetime.strptime(i, "%H:%M:%S.%f") for i in x])
y = y.astype(float)
plt.plot(x,y)
plt.gcf().autofmt_xdate()
plt.show()
Concerning the ticking of the axes: In order to have ticks every half a second you can use a MicrosecondLocator with an interval of 500000.
import matplotlib.dates
# ...
loc = matplotlib.dates.MicrosecondLocator(500000)
plt.gca().xaxis.set_major_locator(loc)
plt.gca().xaxis.set_major_formatter(matplotlib.dates.AutoDateFormatter(loc))
from datetime import datetime
import datetime as dt
import csv
import matplotlib.dates as mdates
import numpy as np
import matplotlib.pyplot as plt
ldays = list()
aesvalues = list()
tezvalues = list()
vdevalues = list()
with open('data/dg_year_50.csv', newline='') as csvfile:
has_header = csv.Sniffer().has_header(csvfile.read(1024))
csvfile.seek(0) # Rewind.
datareader = csv.reader(csvfile, delimiter=',', quotechar='|')
if has_header:
next(datareader) # Skip header row.
for row in datareader:
date_cell = row[0]
aes_cell = row[1]
tez_cell = row[2]
vde_cell = row[3]
datetime_object = datetime.strptime(date_cell, '%d.%m.%Y %H:%M:%S')
aesvalues.append(aes_cell)
tezvalues.append(tez_cell)
vdevalues.append(tez_cell)
ldays.append(datetime_object)
days = mdates.date2num(np.array(ldays))
s_aesvalues = sorted(list(map(int, aesvalues)))
s_tezvalues = sorted(list(map(int, tezvalues)))
s_vdevalues = sorted(list(map(int, vdevalues)))
# These are the colors that will be used in the plot
color_sequence = ['#ffbb78', '#e377c2', '#1f77b4', '#ff7f0e', '#2ca02c',
'#98df8a', '#d62728', '#ff9896', '#9467bd', '#c5b0d5',
'#8c564b', '#c49c94', '#aec7e8', '#e377c2', '#f7b6d2',
'#c7c7c7', '#bcbd22', '#dbdb8d', '#17becf', '#9edae5']
# make a plot
fig, ax = plt.subplots(figsize=(14, 12))
# plot the data
majors = [s_tezvalues, s_vdevalues, s_aesvalues]
for rank, column in enumerate(majors):
line = plt.plot_date(x=days, y=majors[rank], lw=2.5, color=color_sequence[rank])
fig.suptitle('Дані по енергетиці', fontsize=18, ha='center')
plt.xlabel('Дата', fontsize=14, ha='center')
plt.ylabel('Кількість енергії (Вт)', fontsize=14, ha='center')
plt.show()
I have 'data/dg_year_50.csv' with 4 columns (Дата,АЕС,ТЕЦ,ВДЕ).
First one stands for "Date" and rest 3 for the appropriate values that needs to be visualized as a lines in plot.
I do not understand why I'm getting visualized 2 lines instead of 3.
The result visualization looks like this:
I found the mistake, it was in the following string:
vdevalues.append(tez_cell)
It should be changed like this:
vdevalues.append(vde_cell)
And yes, definitely, with pandas solution is much easier:
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
data = pd.read_csv('data/dg_year_50.csv', index_col=0, parse_dates=True).apply(np.int64)
data.plot()
plt.show()
Attaching the result figure:
I have big data as csv file which has too many dates, so when I plot it, x axis writes all of them, like f.e : from 2000-12-24 to 2017-12-24 and also y axis.
I have tried to use a set, but that set needs to sort and problem is that when I sort it the data from Y isn't for any of sorted dates.
import matplotlib.pyplot as plt
import urllib as u
import numpy as np
import csv
stock_price_url = 'https://pythonprogramming.net/yahoo_finance_replacement'
date = []
openp = []
high = []
low = []
close = []
adjclose = []
volume = []
text = u.request.urlopen(stock_price_url).read().decode()
with open('nw.csv', 'w') as fw:
fw.write(text)
fw.close()
with open('nw.csv', 'r') as csvf:
f = csv.reader(csvf, delimiter=',')
for row in f:
if 'Date' not in row:
date.append(row[0])
openp.append(row[1])
high.append(row[2])
low.append(row[3])
close.append(row[4])
adjclose.append(row[5])
volume.append(row[6])
dateset = set([])
for z in date:
dateset.add(z[:4])
highset = []
for z in high:
highset.append(z[:3])
plt.plot(set(dateset), set(highset), linewidth=0.5)
plt.show()
You need to convert the dates first into a Python datetime object. This can then be converted into a matplotlib number. With this you can then tell matplotlib to add ticks based on year or month changes:
from datetime import datetime
import matplotlib
import matplotlib.pyplot as plt
import urllib as u
import numpy as np
import csv
stock_price_url = 'https://pythonprogramming.net/yahoo_finance_replacement'
date = []
high = []
text = u.request.urlopen(stock_price_url).read().decode()
with open('nw.csv', 'w') as f_nw:
f_nw.write(text)
with open('nw.csv', 'r', newline='') as f_nw:
csv_nw = csv.reader(f_nw)
header = next(csv_nw)
for row in csv_nw:
date.append(matplotlib.dates.date2num(datetime.strptime(row[0], '%Y-%m-%d')))
high.append(row[2])
ax = plt.gca()
#ax.xaxis.set_minor_locator(matplotlib.dates.MonthLocator([1, 7]))
#ax.xaxis.set_minor_formatter(matplotlib.dates.DateFormatter('%b'))
ax.xaxis.set_major_locator(matplotlib.dates.YearLocator())
ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%Y'))
#ax.tick_params(pad=20)
plt.plot(date, high, linewidth=0.5)
plt.show()
This would give you just the years:
Or if you uncomment the minor locator/formatter you would get:
Note:
You do not need to close a file if you are opening it with a with block.
The script assumes you are using Python 3.x.
To skip the header just read it in using next() before iterating over the rows in your for loop.