How to format Pandas / Matplotlib graph so the x-axis ticks are ONLY hours and minutes?

Question

I am trying to plot temperature with respect to time data from a csv file.

My goal is to have a graph which shows the temperature data per day.

My problem is the x-axis: I would like to show the time for uniformly and only be in hours and minutes with 15 minute intervals, for example: 00:00 , 00:15 , 00:30 .

The csv is loaded into a pandas dataframe, where I filter the data to be shown based on what day it is, in the code I want only temperature data for 18th day of the month.

Here is the csv data that I am loading in:

date,temp,humid
2020-10-17 23:50:02,20.57,87.5
2020-10-17 23:55:02,20.57,87.5
2020-10-18 00:00:02,20.55,87.31
2020-10-18 00:05:02,20.54,87.17
2020-10-18 00:10:02,20.54,87.16
2020-10-18 00:15:02,20.52,87.22
2020-10-18 00:20:02,20.5,87.24
2020-10-18 00:25:02,20.5,87.24

here is the python code to make the graph:

import pandas as pd
import datetime
import matplotlib.pyplot as plt

df = pd.read_csv("saveData2020.csv")

#make new columns in dataframe so data can be filtered
df["New_Date"] = pd.to_datetime(df["date"]).dt.date
df["New_Time"] = pd.to_datetime(df["date"]).dt.time
df["New_hrs"] = pd.to_datetime(df["date"]).dt.hour
df["New_mins"] = pd.to_datetime(df["date"]).dt.minute
df["day"] = pd.DatetimeIndex(df['New_Date']).day

#filter the data to be only day 18
ndf = df[df["day"]==18]

#display dataframe in console
pd.set_option('display.max_rows', ndf.shape[0]+1)
print(ndf.head(10))

#plot a graph
ndf.plot(kind='line',x='New_Time',y='temp',color='red')

#edit graph to be sexy
plt.setp(plt.gca().xaxis.get_majorticklabels(),'rotation', 30)
plt.xlabel("time")
plt.ylabel("temp in C")

#show graph with the sexiness edits
plt.show()

here is the graph I get:

Answer 1

Answer

First of all, you have to convert "New Time" (your x axis) from str to datetime type with:

ndf["New_Time"] = pd.to_datetime(ndf["New_Time"], format = "%H:%M:%S")

Then you can simply add this line of code before showing the plot (and import the proper matplotlib library, matplotlib.dates as md ) to tell matplotlib you want only hours and minutes:

plt.gca().xaxis.set_major_formatter(md.DateFormatter('%H:%M'))

And this line of code to fix the 15 minutes span for the ticks:

plt.gca().xaxis.set_major_locator(md.MinuteLocator(byminute = [0, 15, 30, 45]))

For more info on x axis time formatting you can check this answer .

Code

import pandas as pd
import datetime
import matplotlib.pyplot as plt
import matplotlib.dates as md

df = pd.read_csv("saveData2020.csv")


#make new columns in dataframe so data can be filtered
df["New_Date"] = pd.to_datetime(df["date"]).dt.date
df["New_Time"] = pd.to_datetime(df["date"]).dt.time
df["New_hrs"] = pd.to_datetime(df["date"]).dt.hour
df["New_mins"] = pd.to_datetime(df["date"]).dt.minute
df["day"] = pd.DatetimeIndex(df['New_Date']).day

#filter the data to be only day 18
ndf = df[df["day"]==18]
ndf["New_Time"] = pd.to_datetime(ndf["New_Time"], format = "%H:%M:%S")

#display dataframe in console
pd.set_option('display.max_rows', ndf.shape[0]+1)
print(ndf.head(10))

#plot a graph
ndf.plot(kind='line',x='New_Time',y='temp',color='red')

#edit graph to be sexy
plt.setp(plt.gca().xaxis.get_majorticklabels(),'rotation', 30)
plt.xlabel("time")
plt.ylabel("temp in C")

plt.gca().xaxis.set_major_locator(md.MinuteLocator(byminute = [0, 15, 30, 45]))
plt.gca().xaxis.set_major_formatter(md.DateFormatter('%H:%M'))

#show graph with the sexiness edits
plt.show()

Plot

Notes

If you do not need "New_Date" , "New_Time" , "New hrs" , "New_mins" and "day" columns for other purposes than plotting, you can use a shorter version of the above code, getting rid of those columns and appling the day filter directly on "date" column as here:

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as md

df = pd.read_csv("saveData2020.csv")

# convert date from string to datetime
df["date"] = pd.to_datetime(df["date"], format = "%Y-%m-%d %H:%M:%S")

#filter the data to be only day 18
ndf = df[df["date"].dt.day == 18]

#display dataframe in console
pd.set_option('display.max_rows', ndf.shape[0]+1)
print(ndf.head(10))

#plot a graph
ndf.plot(kind='line',x='date',y='temp',color='red')

#edit graph to be sexy
plt.setp(plt.gca().xaxis.get_majorticklabels(),'rotation', 30)
plt.xlabel("time")
plt.ylabel("temp in C")

plt.gca().xaxis.set_major_locator(md.MinuteLocator(byminute = [0, 15, 30, 45]))
plt.gca().xaxis.set_major_formatter(md.DateFormatter('%H:%M'))

#show graph with the sexiness edits
plt.show()

This code will reproduce exactly the same plot as before.