Reputation: 109
I am trying to plot some data, but I don't know how I can add the date values on the x-axis on my graph. Here is my code:
import pandas as pd
import numpy as np
%matplotlib inline
%pylab inline
import matplotlib.pyplot as plt
pylab.rcParams['figure.figsize'] = (15, 9)
df["msft"].plot(grid = True)
The description of the image is a plot, but the x-axis just has numbers, but I am looking for dates to appear on x-axis. The dates are in the date column in the dataframe.
Here is what the dataframe looks like:
date msft nok aapl ibm amzn
1 2018-01-01 09:00:00 112 1 143 130 1298
2 2018-01-01 10:00:00 109 10 185 137 1647
3 2018-01-01 11:00:00 98 11 146 105 1331
4 2018-01-01 12:00:00 83 3 214 131 1355
Can you offer some help on what I am missing?
Upvotes: 2
Views: 290
Reputation: 1281
one way to do it is the set_xticklabels
function, though Mr. T's answer is the proper way to go
ax = plt.subplot(111)
df["msft"].plot(grid = True)
ax.set_xticklabels(df['date'])
plt.xticks(np.arange(4))
with the data provided:
Upvotes: -1
Reputation: 12410
Your column date
is just another column for pandas, you have to tell the program that you want to plot against this specific one. One way is to plot against this column:
from matplotlib import pyplot as plt
import pandas as pd
#load dataframe
df = pd.read_csv("test.txt", delim_whitespace=True)
#convert date column to datetime object, if it is not already one
df["date"] = pd.to_datetime(df["date"])
#plot the specified columns vs dates
df.plot(x = "date", y = ["msft", "ibm"], kind = "line", grid = True)
plt.show()
For more pandas plot options, please have a look at the documentation.
Another way would be to set date
as the index of the dataframe. Then you can use your approach:
df.set_index("date", inplace = True)
df[["msft", "ibm"]].plot(grid = True)
plt.show()
The automatic date labels might not be, what you want to display. But there are ways to format the output and you can find examples on SO.
Upvotes: 2