I am trying to plot multiple graphs in one figure using subplots. It looks the way I want but the data on x-axis is wrong. Instead of taking the values of ‘Time’ it is taking the number of indices of the csv file imported using pandas. The time is from 0 to 7 milliseconds only. csv is imported as 200000 rows and 5 columns which includes a column for index numbers and 4 columns which I want to use to plot. I have attached my code. could someone help me figure it out?
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import pandas as pd2
import numpy as np3
import matplotlib.pyplot as plt4
from pathlib import Path 5
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def function(x,y,z,v,Plot_ShareY=True): #x, y, z, v is filename 8
data_1 = Path(x) #stores the relative path location9
data_2 = Path(y)10
data_3 = Path(z)11
data_4 = Path(v)12
print(data_1) #prints the file location for each input argument13
print(data_2)14
print(data_3)15
print(data_4)16
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x1 = pd.read_csv(data_1, delimiter=";", skiprows=(1), decimal = ",", na_values = ['no info', '.']) #loads the csv file from the path created above18
y1 = pd.read_csv(data_2, delimiter=";", skiprows=(1), decimal = ",", na_values = ['no info', '.'])19
z1 = pd.read_csv(data_3, delimiter=";", skiprows=(1), decimal = ",", na_values = ['no info', '.'])20
v1 = pd.read_csv(data_4, delimiter=";", skiprows=(1), decimal = ",", na_values = ['no info', '.'])21
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time1 = x1.iloc[:,0]23
time2 = y1.iloc[:,0]24
time3 = z1.iloc[:,0]25
time4 = v1.iloc[:,0]26
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resA_x1 = x1.iloc[:,1]28
resB_x1 = x1.iloc[:,2]29
resC_x1 = x1.iloc[:,3]30
resD_x1 = x1.iloc[:,4]31
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resA_y1 = y1.iloc[:,1]33
resB_y1 = y1.iloc[:,2]34
resC_y1 = y1.iloc[:,3]35
resD_y1 = y1.iloc[:,4]36
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resA_z1 = z1.iloc[:,1]38
resB_z1 = z1.iloc[:,2]39
resC_z1 = z1.iloc[:,3]40
resD_z1 = z1.iloc[:,4]41
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resA_v1 = v1.iloc[:,1]43
resB_v1 = v1.iloc[:,2]44
resC_v1 = v1.iloc[:,3]45
resD_v1 = v1.iloc[:,4]46
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fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1, figsize=(12,8))49
fig.suptitle('Drops') 50
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ax1.plot(time1, resA_x1, 'r', resB_x1, 'g', resC_x1, 'b', resD_x1, 'y')52
ax1.set_ylabel('A [V]')53
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ax2.plot(time2, resA_y1, 'r', resB_y1, 'g', resC_y1, 'b', resD_y1, 'y')55
ax2.set_ylabel('B [V]') 56
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ax3.plot(time3, resA_z1, 'r', resB_z1, 'g', resC_z1, 'b', resD_z1, 'y')58
ax3.set_ylabel('C [V]')59
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ax4.plot(time4, resA_v1, 'r', resB_v1, 'g', resC_v1, 'b', resD_v1, 'y')61
ax4.set_xlabel('Time [s]')62
ax4.set_ylabel('D [V]') 63
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function('above-1-cm-A1-3.csv','above-1-cm-B2-1.csv', 'above-1-cm-C3-1.csv', 'above-1-cm-D4-1.csv')66
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Answer
You need to specify the same x-axis for each of the datasets:
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import pandas as pd2
import numpy as np3
import matplotlib.pyplot as plt4
from pathlib import Path 5
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def function(x,y,z,v,Plot_ShareY=True): #x, y, z, v is filename 7
data_1 = Path(x) #stores the relative path location8
data_2 = Path(y)9
data_3 = Path(z)10
data_4 = Path(v)11
print(data_1) #prints the file location for each input argument12
print(data_2)13
print(data_3)14
print(data_4)15
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#loads the csv file from the path created above17
x1 = pd.read_csv(data_1, delimiter=";", skiprows=(1, 2), decimal=",", na_values=['no info', '.']) 18
y1 = pd.read_csv(data_2, delimiter=";", skiprows=(1, 2), decimal=",", na_values=['no info', '.'])19
z1 = pd.read_csv(data_3, delimiter=";", skiprows=(1, 2), decimal=",", na_values=['no info', '.'])20
v1 = pd.read_csv(data_4, delimiter=";", skiprows=(1, 2), decimal=",", na_values=['no info', '.'])21
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time1 = x1['Time']23
time2 = y1['Time']24
time3 = z1['Time']25
time4 = v1['Time']26
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resA_x1 = x1['Channel A']28
resB_x1 = x1['Channel B']29
resC_x1 = x1['Channel C']30
resD_x1 = x1['Channel D']31
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resA_y1 = y1['Channel A']33
resB_y1 = y1['Channel B']34
resC_y1 = y1['Channel C']35
resD_y1 = y1['Channel D']36
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resA_z1 = z1['Channel A']38
resB_z1 = z1['Channel B']39
resC_z1 = z1['Channel C']40
resD_z1 = z1['Channel D']41
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resA_v1 = v1['Channel A']43
resB_v1 = v1['Channel B']44
resC_v1 = v1['Channel C']45
resD_v1 = v1['Channel D']46
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fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1, figsize=(12,8))48
fig.suptitle('Drops') 49
ax1.plot(time1, resA_x1, 'r', time1, resB_x1, 'g', time1, resC_x1, 'b', time1, resD_x1, 'y')50
ax1.set_ylabel('A [V]')51
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ax2.plot(time2, resA_y1, 'r', time2, resB_y1, 'g', time2, resC_y1, 'b', time2, resD_y1, 'y')53
ax2.set_ylabel('B [V]') 54
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ax3.plot(time3, resA_z1, 'r', time3, resB_z1, 'g', time3, resC_z1, 'b', time3, resD_z1, 'y')56
ax3.set_ylabel('C [V]')57
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ax4.plot(time4, resA_v1, 'r', time4, resB_v1, 'g', time4, resC_v1, 'b', time4, resD_v1, 'y')59
ax4.set_ylabel('D [V]') 60
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plt.show()62
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function('trial.csv', 'trial.csv', 'trial.csv', 'trial.csv') 64
Giving you:
If you also use skiprows=(1, 2), the header columns can also be used.
This could be fully generalised to allow different numbers of CSV files to be passed:
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import pandas as pd2
import numpy as np3
import matplotlib.pyplot as plt4
from pathlib import Path 5
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def function(*xyzv, Plot_ShareY=True): #x, y, z, v is filename 7
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# data paths9
dps = [Path(f) for f in xyzv]10
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for dp in dps:12
print(dp)13
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#dataframes - loads the csv file from the paths created above15
dfs = [pd.read_csv(dp, delimiter=";", skiprows=(1, 2), decimal=",", na_values=['no info', '.']) for dp in dps]16
times = [df['Time'] for df in dfs]17
y_labels = [f'{dp} [V]' for dp in dps] # e.g. base it on the filename18
ch = [('Channel A', 'r'), ('Channel B', 'g'), ('Channel C', 'b'), ('Channel D', 'y')] 19
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fig, *axes = plt.subplots(len(dfs), 1, figsize=(12, 8))21
fig.suptitle('Drops') 22
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for x, ax, df, y_label in zip(times, axes[0], dfs, y_labels):24
for channel, colour in ch:25
ax.plot(x, df[channel], colour)26
ax.set_ylabel(y_label)27
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plt.show()29
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function('trial.csv', 'trial.csv', 'trial.csv', 'trial.csv') 31
function('trial.csv', 'trial.csv') 32