The code I have to read and plot data from my excel file is this:
import pandas as pd
import matplotlib.pyplot as plt
excel_file = 'file1.xlsx'
file1 = pd.read_excel(excel_file)
file1.head()
plt.plot(x,y1,y2)
plt.xlabel('wavelenghts')
plt.ylabel('reflectivity')
plt.legend(loc='upper left')
plt.show
It works.
The questions are:
I have more columns, but when I want to add y3, y4,... I get the error that y3 is undefined.
In legend I want to change the name of y1 to CK4/5-PCA82500 and others as well. Is there any way to do it?
f, ax = figure()
plt.plot(file1.x,file1.y1,label='')
plt.plot(file1.x,file1.y2)
plt.plot(file1.x,file1.y3)
.....
plt.xlabel('wavelenghts')
plt.ylabel('reflectivity')
plt.legend(loc='upper left')
plt.show
Related
import matplotlib.pyplot
plt.figure()
plt.plot(x, 'r+', label='one')
plt.plot(x1, 'go--', label ='two')
plt.plot(y, 'ro', label='Three')
plt.legend()
In the above code legend marker is 'r+' , 'go--' and 'ro' but I want it to change into 1,2 and 3 as there are 3 plots.? Can anyone help me in solving this issue? Also is there any anyway it can be done without hardcoding the numbers? """
Thank you.
You could use a generator (e.g., itertools.count) and next:
import matplotlib.pyplot
x=x1=y=(0,0) # dummy data
markers = iter(['r+', 'go--', 'ro'])
plt.figure()
plt.plot(x, next(markers), label='1')
plt.plot(x1, next(markers), label='2')
plt.plot(y, next(markers), label='3')
plt.legend()
output:
I have dataframe like this:
df_meshX_min_select = pd.DataFrame({
'Number of Elements' : [5674, 8810,13366,19751,36491],
'Time (a)' : [42.14, 51.14, 55.64, 55.14, 56.64],
'Different Result(Temperature)' : [0.083849, 0.057309, 0.055333, 0.060516, 0.035343]})
and I tried to combine bar plot (number of elements Vs Different result) and line plot (Number of elements Vs Time) in the same figure, but I found the following problem like this:
it seems that x_value doesn't match when combining 2 plots, but if you see the data frame, the x value is exactly the same value.
My expectation is combining these 2 plots into 1 figure:
and this is the code that I made:
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
df_meshX_min_select = pd.DataFrame({
'Number of Elements' : [5674, 8810,13366,19751,36491],
'Time (a)' : [42.14, 51.14, 55.64, 55.14, 56.64],
'Different Result(Temperature)' : [0.083849, 0.057309, 0.055333, 0.060516, 0.035343]})
x1= df_meshX_min_select["Number of Elements"]
t1= df_meshX_min_select["Time (a)"]
T1= df_meshX_min_select["Different Result(Temperature)"]
#Create combo chart
fig, ax1 = plt.subplots(figsize=(10,6))
color = 'tab:green'
#bar plot creation
ax1.set_title('Mesh Analysis', fontsize=16)
ax1.set_xlabel('Number of elements', fontsize=16)
ax1.set_ylabel('Different Result(Temperature)', fontsize=16)
ax1 = sns.barplot(x='Number of Elements', y='Different Result(Temperature)', data = df_meshX_min_select)
ax1.tick_params(axis='y')
#specify we want to share the same x-axis
ax2 = ax1.twinx()
color = 'tab:red'
#line plot creation
ax2.set_ylabel('Time (a)', fontsize=16)
ax2 = sns.lineplot(x='Number of Elements', y='Time (a)', data = df_meshX_min_select, sort=False, color=color, ax=ax2)
ax2.tick_params(axis='y', color=color)
#show plot
plt.show()
Anyone can help me, please?
Seaborn and pandas use a categorical x-axis for bar plots (internally numbered 0,1,2,...) and floating-point numbers for a line plot. Note that your x-values aren't evenly spaced, so either the bars would have weird distances between them, or wouldn't align with the x-values from the line plot.
Here is a solution using standard matplotlib to combine both graphs.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
df_meshx_min_select = pd.DataFrame({
'number of elements': [5674, 8810, 13366, 19751, 36491],
'time (a)': [42.14, 51.14, 55.64, 55.14, 56.64],
'different result(temperature)': [0.083849, 0.057309, 0.055333, 0.060516, 0.035343]})
x1 = df_meshx_min_select["number of elements"]
t1 = df_meshx_min_select["time (a)"]
d1 = df_meshx_min_select["different result(temperature)"]
fig, ax1 = plt.subplots(figsize=(10, 6))
color = 'limegreen'
ax1.set_title('mesh analysis', fontsize=16)
ax1.set_xlabel('number of elements', fontsize=16)
ax1.set_ylabel('different result(temperature)', fontsize=16, color=color)
ax1.bar(x1, height=d1, width=2000, color=color)
ax1.tick_params(axis='y', colors=color)
ax2 = ax1.twinx() # share the x-axis, new y-axis
color = 'crimson'
ax2.set_ylabel('time (a)', fontsize=16, color=color)
ax2.plot(x1, t1, color=color)
ax2.tick_params(axis='y', colors=color)
plt.show()
I was plotting a boxplot with a lineplot and I had the same problem even my two x-axes are identical, so I solved converting my x-axis feature to type string:
df_meshX_min_select['Number of Elements'] = df_meshX_min_select['Number of Elements'].astype('string')
This way the plot works using seaborn:
I want to make the dates on the x- axis look more prettier, currently the dates cannot be even read. what is the best way to do it.
Below is the code and also the actual graph picture
import matplotlib.pyplot as plt
import pandas as pd
import pandas as pd
df = dataset
# gca stands for 'get current axis'
ax = plt.gca()
y1 = df['Predicted_Lower']
y2 = df['Predicted_Upper']
x = df['Date']
ax.fill_between(x,y1, y2, facecolor="#CC6666", alpha=0.7)
df.plot(kind='line',x='Date',y='Predicted_Lower',color='white',ax=ax)
df.plot(kind='line',x='Date',y='Predicted_Upper',color='white', ax=ax)
df.plot(kind='line',x='Date',y='Predicted', color='yellow', ax=ax)
df.plot(kind='line',x='Date',y='Actuals', color='green', ax=ax)
plt.xticks(rotation=45)
plt.show()
You can modify the number of labels, by settings locs and labels parameters using matplotlib.pyplot.xticks, for example get the current locs and labels and only plot one-third of them:
# ...
df.plot(kind='line',x='Date',y='Actuals', color='green', ax=ax)
locs, labels = plt.xticks()
plt.xticks(locs[::3], labels[::3], rotation=45)
plt.show()
I'm using matplotlib.axes.Axes.twinx to have a shared x-axis in matplotlib for both . I dont know why instead of 13 bars to be plotted, only 12 of them are getting plotted.
Link of Data set
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
dataFrame=pd.read_csv("NEM.csv",sep=',')
dataFrame['ratio']=dataFrame['Expert']/dataFrame['Novice']
fig, ax1 = plt.subplots(figsize=(9, 6))
ax1.set_title('N-E Analysis')
xticklabels=dataFrame['Task'].tolist()
ax1.plot('Novice', data=dataFrame, marker='', color='dodgerblue', linewidth=2,label='Novice',zorder=100)
ax1.plot('Expert', data=dataFrame, marker='', color='darkorange', linewidth=2,label='Expert',zorder=200)
plt.ylim(0,120)
ax2 = ax1.twinx()
ax2.bar('Task','ratio', data=dataFrame, color='gray',width=0.35,label='NE',zorder=0)
ax1.spines['top'].set_visible(False)
ax1.spines['right'].set_visible(False)
ax1.spines['left'].set_visible(False)
ax2.spines['top'].set_visible(False)
ax2.spines['right'].set_visible(False)
ax2.spines['left'].set_visible(False)
ax1.set_xticklabels(xticklabels, rotation = 45, ha="right")
ax1.yaxis.grid()
ax1.tick_params(left='off',bottom='off')
ax2.tick_params(right='off')
plt.ylim(0,12)
h1, l1 = ax1.get_legend_handles_labels()
h2, l2 = ax2.get_legend_handles_labels()
p=ax1.legend(h2+h1, l2+l1, loc=2,frameon=False)
fig.tight_layout()
plt.show()
When using plots, it could be good practice to say explicitily how many bars or points you are going to plot. For instance, you can create an x-axis this way:
x_axis = np.arange(len(dataFrame[Task].tolist())
then:
ax1.plot(x_axis, dataFrame['Novice'].tolist(), ...)
after that you rename the xticklabels like this:
ax1.set_xticks(x_axis)
ax1.set_xticklabels(dataFrame[Task].tolist())
Do the same with the bar graph:
ax2.bar(x_axis, dataFrame['Ratio'].tolist(), ...)
This should do the trick.
Hope it helps.
I am trying to create a 3D Temperature plot vs Depth vs Time with a large .csv data-set. The example below is created in matlab. I want a similar output using Python 3.x with reverse scales on the Temperature and Depth axis.
Example output with a few mods needed
I have started off with the following code:
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
# Get the data (csv file is hosted on the web)
data = pd.read_csv('C;\\Path\\TestData_Temp-Time-Depth_3DPlot.csv')
# Transform it to a long format
df = data.unstack().reset_index()
df.columns = ["X", "Y", "Z"]
# And transform the old column name in something numeric
df['X'] = pd.Categorical(df['X'])
df['X'] = df['X'].cat.codes
# Make the plot
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.plot_trisurf(df['Y'], df['X'], df['Z'], cmap=plt.cm.jet, linewidth=0.2)
plt.show()
# to Add a color bar which maps values to colors.
surf = ax.plot_trisurf(df['Y'], df['X'], df['Z'], cmap=plt.cm.jet, linewidth=0.2)
fig.colorbar(surf, shrink=0.5, aspect=5)
plt.show()
# Rotate it
ax.view_init(30, 45)
plt.show()
# Other palette
ax.plot_trisurf(df['Y'], df['X'], df['Z'], cmap=plt.cm.jet, linewidth=0.01)
plt.show()
I am having issues understanding how to assign values from from csv to the x, y, z axis.
The example data I am using is formatted like:
csv data structure
Example data download: Download Example Data
Thank you in advance.