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?
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from pathlib import Path
def function(x,y,z,v,Plot_ShareY=True): #x, y, z, v is filename
data_1 = Path(x) #stores the relative path location
data_2 = Path(y)
data_3 = Path(z)
data_4 = Path(v)
print(data_1) #prints the file location for each input argument
print(data_2)
print(data_3)
print(data_4)
x1 = pd.read_csv(data_1, delimiter=";", skiprows=(1), decimal = ",", na_values = ['no info', '.']) #loads the csv file from the path created above
y1 = pd.read_csv(data_2, delimiter=";", skiprows=(1), decimal = ",", na_values = ['no info', '.'])
z1 = pd.read_csv(data_3, delimiter=";", skiprows=(1), decimal = ",", na_values = ['no info', '.'])
v1 = pd.read_csv(data_4, delimiter=";", skiprows=(1), decimal = ",", na_values = ['no info', '.'])
time1 = x1.iloc[:,0]
time2 = y1.iloc[:,0]
time3 = z1.iloc[:,0]
time4 = v1.iloc[:,0]
resA_x1 = x1.iloc[:,1]
resB_x1 = x1.iloc[:,2]
resC_x1 = x1.iloc[:,3]
resD_x1 = x1.iloc[:,4]
resA_y1 = y1.iloc[:,1]
resB_y1 = y1.iloc[:,2]
resC_y1 = y1.iloc[:,3]
resD_y1 = y1.iloc[:,4]
resA_z1 = z1.iloc[:,1]
resB_z1 = z1.iloc[:,2]
resC_z1 = z1.iloc[:,3]
resD_z1 = z1.iloc[:,4]
resA_v1 = v1.iloc[:,1]
resB_v1 = v1.iloc[:,2]
resC_v1 = v1.iloc[:,3]
resD_v1 = v1.iloc[:,4]
fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1, figsize=(12,8))
fig.suptitle('Drops')
ax1.plot(time1, resA_x1, 'r', resB_x1, 'g', resC_x1, 'b', resD_x1, 'y')
ax1.set_ylabel('A [V]')
ax2.plot(time2, resA_y1, 'r', resB_y1, 'g', resC_y1, 'b', resD_y1, 'y')
ax2.set_ylabel('B [V]')
ax3.plot(time3, resA_z1, 'r', resB_z1, 'g', resC_z1, 'b', resD_z1, 'y')
ax3.set_ylabel('C [V]')
ax4.plot(time4, resA_v1, 'r', resB_v1, 'g', resC_v1, 'b', resD_v1, 'y')
ax4.set_xlabel('Time [s]')
ax4.set_ylabel('D [V]')
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')
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Answer
You need to specify the same x-axis for each of the datasets:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from pathlib import Path
def function(x,y,z,v,Plot_ShareY=True): #x, y, z, v is filename
data_1 = Path(x) #stores the relative path location
data_2 = Path(y)
data_3 = Path(z)
data_4 = Path(v)
print(data_1) #prints the file location for each input argument
print(data_2)
print(data_3)
print(data_4)
#loads the csv file from the path created above
x1 = pd.read_csv(data_1, delimiter=";", skiprows=(1, 2), decimal=",", na_values=['no info', '.'])
y1 = pd.read_csv(data_2, delimiter=";", skiprows=(1, 2), decimal=",", na_values=['no info', '.'])
z1 = pd.read_csv(data_3, delimiter=";", skiprows=(1, 2), decimal=",", na_values=['no info', '.'])
v1 = pd.read_csv(data_4, delimiter=";", skiprows=(1, 2), decimal=",", na_values=['no info', '.'])
time1 = x1['Time']
time2 = y1['Time']
time3 = z1['Time']
time4 = v1['Time']
resA_x1 = x1['Channel A']
resB_x1 = x1['Channel B']
resC_x1 = x1['Channel C']
resD_x1 = x1['Channel D']
resA_y1 = y1['Channel A']
resB_y1 = y1['Channel B']
resC_y1 = y1['Channel C']
resD_y1 = y1['Channel D']
resA_z1 = z1['Channel A']
resB_z1 = z1['Channel B']
resC_z1 = z1['Channel C']
resD_z1 = z1['Channel D']
resA_v1 = v1['Channel A']
resB_v1 = v1['Channel B']
resC_v1 = v1['Channel C']
resD_v1 = v1['Channel D']
fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1, figsize=(12,8))
fig.suptitle('Drops')
ax1.plot(time1, resA_x1, 'r', time1, resB_x1, 'g', time1, resC_x1, 'b', time1, resD_x1, 'y')
ax1.set_ylabel('A [V]')
ax2.plot(time2, resA_y1, 'r', time2, resB_y1, 'g', time2, resC_y1, 'b', time2, resD_y1, 'y')
ax2.set_ylabel('B [V]')
ax3.plot(time3, resA_z1, 'r', time3, resB_z1, 'g', time3, resC_z1, 'b', time3, resD_z1, 'y')
ax3.set_ylabel('C [V]')
ax4.plot(time4, resA_v1, 'r', time4, resB_v1, 'g', time4, resC_v1, 'b', time4, resD_v1, 'y')
ax4.set_ylabel('D [V]')
plt.show()
function('trial.csv', 'trial.csv', 'trial.csv', 'trial.csv')
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:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from pathlib import Path
def function(*xyzv, Plot_ShareY=True): #x, y, z, v is filename
# data paths
dps = [Path(f) for f in xyzv]
for dp in dps:
print(dp)
#dataframes - loads the csv file from the paths created above
dfs = [pd.read_csv(dp, delimiter=";", skiprows=(1, 2), decimal=",", na_values=['no info', '.']) for dp in dps]
times = [df['Time'] for df in dfs]
y_labels = [f'{dp} [V]' for dp in dps] # e.g. base it on the filename
ch = [('Channel A', 'r'), ('Channel B', 'g'), ('Channel C', 'b'), ('Channel D', 'y')]
fig, *axes = plt.subplots(len(dfs), 1, figsize=(12, 8))
fig.suptitle('Drops')
for x, ax, df, y_label in zip(times, axes[0], dfs, y_labels):
for channel, colour in ch:
ax.plot(x, df[channel], colour)
ax.set_ylabel(y_label)
plt.show()
function('trial.csv', 'trial.csv', 'trial.csv', 'trial.csv')
function('trial.csv', 'trial.csv')