I have a sample text file as follows:(test.txt)
06:00:41 2
06:10:41 4
06:20:41 6
06:25:41 8
I want to plot this taking time value for X-Axis and the 2nd column to the y axis.
import matplotlib.pyplot as plt
import datetime
import matplotlib.dates as mdates
import time
import numpy as np
f2 = open('test.txt', 'r')
lines = f2.readlines()
f2.close()
x1 = []
y1 = []
for line in lines:
p = line.split()
a = time.strptime((p[0]),"%H:%M:%S")
x1.append((a))
y1.append(float(p[1]))
xv = np.array(x1)
yv = np.array(y1)
plt.plot(xv, yv)
plt.show()
This is how I plot it. But the X-Axis shows 500,1000,1500 etc. Instead I want to show the time values as 06:00:41,06:10:41,06:20:41 etc. Please help me?
Have you tried plot_date?
It may help if you put your time series data as datetime values
from datetime import datetime
for line in lines:
p = line.split()
xv.append(datetime.strptime(p[0], '%H:%M:%S'))
fig, ax = plt.subplots()
ax.plot_date(xv, yv)
If you want a line plot, try changing the linestyle (docs)
ax.plot_date(xv, yv, linestyle='-')
Related
I have a dataframe and I want to show them on graph. When I start my code, the x and y axis are non-sequential. How can I solve it? Also I give a example graph on picture. First image is mine, the second one is what I want.
This is my code:
from datetime import timedelta, date
import datetime as dt #date analyse
import matplotlib.pyplot as plt
import pandas as pd #read file
def daterange(date1, date2):
for n in range(int ((date2 - date1).days)+1):
yield date1 + timedelta(n)
tarih="01-01-2021"
tarih2="20-06-2021"
start=dt.datetime.strptime(tarih, '%d-%m-%Y')
end=dt.datetime.strptime(tarih2, '%d-%m-%Y')
fg=pd.DataFrame()
liste=[]
tarih=[]
for dt in daterange(start, end):
dates=dt.strftime("%d-%m-%Y")
with open("fng_value.txt", "r") as filestream:
for line in filestream:
date = line.split(",")[0]
if dates == date:
fng_value=line.split(",")[1]
liste.append(fng_value)
tarih.append(dates)
fg['date']=tarih
fg['fg_value']=liste
print(fg.head())
plt.subplots(figsize=(20, 10))
plt.plot(fg.date,fg.fg_value)
plt.title('Fear&Greed Index')
plt.ylabel('Fear&Greed Data')
plt.xlabel('Date')
plt.show()
This is my graph:
This is the graph that I want:
Line plot with datetime x axis
So it appears this code is opening a text file, adding values to either a list of dates or a list of values, and then making a pandas dataframe with those lists. Finally, it plots the date vs values with a line plot.
A few changes should help your graph look a lot better. A lot of this is very basic, and I'd recommend reviewing some matplotlib tutorials. The Real Python tutorial is a good starting place in my opinion.
Fix the y axis limit:
plt.set_ylim(0, 100)
Use a x axis locator from mdates to find better spaced x label locations, it depends on your time range, but I made some data and used day locator.
import matplotlib.dates as mdates
plt.xaxis.set_major_locator(mdates.DayLocator())
Use a scatter plot to add data points as on the linked graph
plt.scatter(x, y ... )
Add a grid
plt.grid(axis='both', color='gray', alpha=0.5)
Rotate the x tick labels
plt.tick_params(axis='x', rotation=45)
I simulated some data and plotted it to look like the plot you linked, this may be helpful for you to work from.
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import matplotlib.dates as mdates
fig, ax = plt.subplots(figsize=(15,5))
x = pd.date_range(start='june 26th 2021', end='july 25th 2021')
rng = np.random.default_rng()
y = rng.integers(low=15, high=25, size=len(x))
ax.plot(x, y, color='gray', linewidth=2)
ax.scatter(x, y, color='gray')
ax.set_ylim(0,100)
ax.grid(axis='both', color='gray', alpha=0.5)
ax.set_yticks(np.arange(0,101, 10))
ax.xaxis.set_major_locator(mdates.DayLocator())
ax.tick_params(axis='x', rotation=45)
ax.set_xlim(min(x), max(x))
I want to draw a graphic with using datas in datetime format as xaxis, but the process lasts very, very, extremly long, over 30 mins there is still no graphic. But once I apply datas in another column, the graphic will occur very soon. All the datas' formats are 'list'.
I'm confused about that, since they are all in the same format, why I can't draw the graphic out using the datetime formate as xaxis??
here is my code, I cherish all your time and help!
from matplotlib import pyplot as plt
import csv
names = []
x = []
y = []
names=[]
with open('all.csv','r') as csvfile: #this csv file contains over 16000 datas
plots= csv.reader(csvfile,delimiter=',')
for row in plots:
x.append(row[1]) #row1 is the datetime format data
y.append(row[2])
print(x,y)
plt.plot(x,y)
plt.show()
Lines of my csv file look something like:
2016/05/02 10:47:45,14.1,20.1,N.C.,170.7,518.3,-1259,-12.61,375.8,44.92,13.76,92.74,132.6,38.86,165.3,170.9,311.5,252.3,501.2,447.2,378.4,35.48,7.868,181.2,
I want the first column as xaxis and the following colums as yaxis...
and the y axis doesn't change, no matter how I change the y axis limit.
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
df = pd.read_csv('all.csv')
x = df.iloc[:,1]
y = df.iloc[:,3]
x = pd.to_datetime(x)
plt.figure(num=3, figsize=(15, 5))
plt.plot(x,y)
my_y_ticks = np.arange(0, 40, 10)
plt.xticks(rotation = 90)
plt.show()
I havent understood exactly what you mean with all the datas' format are list, but I think you could use something like this:
import matplotlib.pyplot as plt
import pandas as pd
df = pd.read_csv('all.csv')
x = df.iloc[:,0]
y = df.iloc[:,1]
x = pd.to_datetime(x)
plt.plot(x,y)
plt.show()
Maybe showing some rows can be useful
EDIT:
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
df = pd.read_csv('all.csv')
x = df.iloc[:,0]
y = df.iloc[:,1]
x = pd.to_datetime(x, format="%Y/%m/%d %H/%M/%S") #if the format is different, change here
fig, ax = plt.subplots()
ax.plot(x, y)
xfmt = mdates.DateFormatter("%Y/%m/%d %H:%M:%S")
ax.xaxis.set_major_formatter(xfmt)
plt.xticks(rotation=70)
plt.show()
I cannot figure this out at all, how do I read a date from csv but I CANNOT represent the date as a label on the x axis. I have tried all the approaches that people have suggested but I cannot get it to work. SO could someone look at the stripped down version of my code and tell me what I am missing please?
a sample of the data being read from csv file
2015-08-04 02:14:05.249392,AA,0.0193103612,0.0193515212,0.0249713335,30.6542480634,30.7195875454,39.640763021,0.2131498442,29.0406746589,13524.5347810182,89,57,99
2015-08-05 02:14:05.325113,AAPL,0.0170506271,0.0137941891,0.0105915637,27.0670313481,21.8975963326,16.8135861893,-19.0986405157,-23.2172064279,21.5647072302,33,26,75
2015-08-06 02:14:05.415193,AIG,0.0080808151,0.0073296055,0.0076213535,12.8278962785,11.635388035,12.0985236788,-9.2962105215,3.980405659,-142.8175077335,71,42,33
2015-08-07 02:14:05.486185,AMZN,0.0235649449,0.0305828226,0.0092703502,37.4081902773,48.5487257749,14.7162247572,29.7810062852,-69.6877219282,-334.0005615016,2,92,10
stripped down code
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.font_manager as fm
ax = plt.subplots(1, 1, figsize=(16, 20), dpi=50) #width height inches
data=np.genfromtxt('/home/dave/Desktop/development/hvanal2015s.csv',
dtype='M8[us],S5,float,float,float',delimiter=',',usecols= [0,1,11,12,13])
my_dates = np.array([d[0] for d in data]).astype('datetime64[D]')
dates = np.unique(my_dates)
print(dates)
x_list = []
y_list = [10,11,12,13]
x_list = dates
plt.plot(x_list,y_list)
plt.title('hv 20 to 10 ranks',fontsize=20)
plt.xlabel('dates')
plt.ylabel('symbol ranks',fontsize=30)
plt.show()
and the output as a png file
matplotlib does not support numpy datetime64 objects, you need to convert it to python datetime object and then select formatter like in code below:
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.font_manager as fm
from datetime import datetime
import matplotlib.dates as mdates
fig,ax = plt.subplots(1, 1) #width height inches
data=np.genfromtxt('data',
dtype='M8[us],S5,float,float,float',delimiter=',',usecols= [0,1,11,12,13])
my_dates = np.array([d[0] for d in data]).astype('datetime64[D]')
dates = np.unique(my_dates)
print(dates)
x_list = []
x_list[:] = dates.astype(datetime)
y_list = [10,11,12,13]
plt.plot(x_list,y_list)
plt.title('hv 20 to 10 ranks',fontsize=20)
plt.xlabel('dates',fontsize=16)
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
plt.ylabel('symbol ranks',fontsize=30)
plt.show()
Here is the plot I have currently:
The 'time' strings I import are like this: 08:12:46, so I would like to cut the zeros at the end, but I can't seem to find the problem. Also, is there a way to show the floats on the Y axis in the exponential format, which is the one I am importing from the csv?
I just started to look into matplotlib and numpy for work, so if you have some advice it would be fantastic.
Thank you in advance!
import numpy as np
import datetime as dt
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib import style
print(plt.style.available)
style.use('ggplot')
fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
def animate(i):
graph_data = open('C:\\Users\\arzuffi pc test\\Desktop\\VMI WIP - Copia (2)\\Cycle info\\_Current Cycle.csv','r').read()
#graph_data = open('C:\\Users\\arzuffi pc test\\Desktop\\Visual Machine Interface Alpha 1.4.3\\Cycle info\\_Current Cycle.csv','r').read()
lines = graph_data.split('\n')
xs = []
ys = []
skip = 0
for line in lines:
if skip < 7:
skip += 1
else:
if len(line) > 1:
time, cycle, pc, pd, co, hv, cr, ph, gd_volt, gd_amp, gd_power, eva_amp, eva_volt, p_rpm, p_amp, r1_rpm, r1_amp, r2_rpm, r2_amp, hmdso, gas, ahc, diff_l, diff_r = line.split(';')
#x, y = line.split(';')
print(time)
print(pc)
xs.append(dt.datetime.strptime(time,'%H:%M:%S'))#.date())
ys.append(pc)
#print(i)
#xs = matplotlib.dates.date2num(xs)
print(xs)
if len (xs) > 100:
xs = xs[-100:]
if len (ys) > 100:
ys = ys[-100:]
ax1.clear()
ax1.plot(xs, ys)
plt.gcf().autofmt_xdate()
ani = animation.FuncAnimation(fig, animate,interval = 1000)
plt.show()
these are the data:
You can specify the format to be used as follows:
xs = matplotlib.dates.date2num(xs) # You need to keep this line
hfmt = matplotlib.dates.DateFormatter('%H:%M:%S')
ax1.xaxis.set_major_formatter(hfmt)
ax1.plot(xs, ys) # You have this already
This would give you an output as follows:
Take a look at this example:
import datetime as dt
from matplotlib import pyplot as plt
import matplotlib.dates as mdates
x = []
d = dt.datetime(2013, 7, 4)
for i in range(30):
d = d+dt.timedelta(days=1)
x.append(d)
y = range(len(x))
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d-%m-%Y'))
plt.gca().xaxis.set_major_locator(mdates.DayLocator())
plt.gcf().autofmt_xdate()
plt.bar(x,y)
plt.show()
The code writes out dates on the x-axis in the plot, see the picture below. The problem is that the dates get clogged up, as seen in the picture. How to make matplotlib to only write out every fifth or every tenth coordinate?
You can specify an interval argument to the DateLocator as in the following. With e.g. interval=5 the locator places ticks at every 5th date. Also, place the autofmt_xdate() after the bar method to get the desired output.
import datetime as dt
from matplotlib import pyplot as plt
import matplotlib.dates as mdates
x = []
d = dt.datetime(2013, 7, 4)
for i in range(30):
d = d+dt.timedelta(days=1)
x.append(d)
y = range(len(x))
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d-%m-%Y'))
plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=5))
plt.bar(x, y, align='center') # center the bars on their x-values
plt.title('DateLocator with interval=5')
plt.gcf().autofmt_xdate()
plt.show()
With interval=3 you will get a tick for every 3rd date: