从 pandas dataframe 中的行创建 X 轴

Question

I'm trying to plot the x-axis from the top row of my dataframe, and the y-axis from another row in my dataframe. My dataframe looks like this:

sector_data =

Time    13:00   13:15   13:30   13:45
Utilities   1235654 1456267 1354894 1423124
Transports  506245  554862  534685  524962
Telecomms   142653  153264  162357  154698

I've tried a lot of different things, with this seeming to make the most sense. But nothing works:

sector_data.plot(kind='line',x='Time',y='Utilities')
plt.show()

I keep getting: KeyError: 'Time'

It should end up looking like this:

Expected Chart

enter image description here

Answer 1

Given the little information you provide I believe this should help:

df = sector_data.T
df.plot(kind='line',x='Time',y='Utilities')
plt.show()

This is how I made a case example (I have already transposed the dataframe)

import pandas as pd
import matplotlib.pyplot as plt
a = {'Time':['13:00','13:15','13:30','13:45'],'Utilities':[1235654,1456267,1354894,1423124],'Transports':[506245,554862,534685,524962],'Telecomms':[142653,153264,162357,154698]}
df = pd.DataFrame(a)
df.plot(kind='line',x='Time',y='Utilities')
plt.show()

Output:

Answer 2

Let's take an example DataFrame:

import pandas as pd
 df = pd.DataFrame({'ColA':['Time','Utilities','Transports','Telecomms'],'ColB':['13:00', 1235654, 506245, 142653],'ColC':['14:00', 1234654, 506145, 142650], 'ColD':['15:00', 4235654, 906245, 142053],'ColE':['16:00', 4205654, 906845, 742053]})
df = df.set_index('ColA') #set index for the column A or the values you want to plot for

Now you can easily plot with matplotlib

plt.plot(df.loc['Time'].values,df.loc['Utilities'].values)