[FIXED] How to reindex, reformat years in graph

Issue

I have data in Excel that have about 68000 index you can check photo see Excel data. Also there is a column named station and this station column has 5 different values (B2,K0,M8,M14,M23,MY2). I have separated all stations where the values ​​in the pressure column are equal to 1. I took the years and temperature of these station values ​​that I reserved as another variable. When I graph them, I get the graph in the photo but as you can see not all year values ​​appear on the x-axis.It goes as 1996-1998-2000.....-2010.

However, I want it to be in the years in between, like 1996-1997-1998 .... 2009 - 2010. How can do this ? Thank you so much.

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

df=pd.read_excel("Julian_iski_data_python.xlsx")

b2_station= df[ ( df["prSM [db]"] == 1) & ( df["Station"] == "B2" ) ]
k0_station= df[ ( df["prSM [db]"] == 1) & ( df["Station"] == "K0" ) ]
m8_station= df[ ( df["prSM [db]"] == 1) & ( df["Station"] == "M8" ) ]
m14_station= df[ ( df["prSM [db]"] == 1) & ( df["Station"] == "M14" ) ]
m23_station= df[ ( df["prSM [db]"] == 1) & ( df["Station"] == "M23" ) ]
my2_station= df[ ( df["prSM [db]"] == 1) & ( df["Station"] == "MY2" ) ]

b2_years= b2_station["yyyy-mm-dd hh:mm:ss.sss"]
b2_temperature= b2_station["T(degC)"]

k0_years= k0_station["yyyy-mm-dd hh:mm:ss.sss"]
k0_temperature= k0_station["T(degC)"]

m8_years = m8_station["yyyy-mm-dd hh:mm:ss.sss"]
m8_temperature= m8_station["T(degC)"]

m14_years = m14_station["yyyy-mm-dd hh:mm:ss.sss"]
m14_temperature= m14_station["T(degC)"]

m23_years = m23_station["yyyy-mm-dd hh:mm:ss.sss"]
m23_temperature= m23_station["T(degC)"]

my2_years = my2_station["yyyy-mm-dd hh:mm:ss.sss"]
my2_temperature= my2_station["T(degC)"]

fig = plt.figure(figsize=(10,10))
axes = fig.add_axes([0.04,0.06,0.95,0.91])


axes.plot(b2_years,b2_temperature,"ro",label="B2")
axes.plot(k0_years,k0_temperature,"b^",label="K0")
axes.plot(m8_years,m8_temperature,"gs",label="M8")
axes.plot(m23_years,m23_temperature,"md",label="M23")
axes.plot(my2_years,my2_temperature,"c*",label="MY2")


axes.set_xlabel("Time")
axes.set_ylabel("Temperature")
axes.legend()

axes.xaxis.grid()
plt.show()

Solution

The ticks are set to default values that is controlled by matplotlib. You can change it using set_major_locator(), specifying the the year frequency of 1. I have a small example below using some dummy data and your code. Check out the last part which sets the tick frequency.

data = {'b2_temperature':np.random.randint(30, size=(175))}
df = pd.DataFrame(data)
df['Date'] = pd.date_range(start='6/1/1996',end='12/31/2010', freq='1M').tolist()
df['Date'] = pd.to_datetime(df['Date'])

fig = plt.figure(figsize=(10,10))
axes = fig.add_axes([0.04,0.06,0.95,0.91])

axes.plot(df['Date'],df['b2_temperature'],"ro",label="B2")

axes.set_xlabel("Time")
axes.set_ylabel("Temperature")
axes.legend()

## NEW CODE ##
import matplotlib.dates as mdates  ## Import required lib
axes.xaxis.set_major_locator(mdates.YearLocator(base=1))   #Setting to years and frequency 1 year
axes.xaxis.set_major_formatter(mdates.DateFormatter('%Y'))     #Formatting to show Years in the labels

axes.xaxis.grid()
plt.show()

PLOT

ADDED REQUIREMENT

As requested, if you are looking to add ticks only in the x-axis for each month, you need to add this line along with the set_major_locator like this.

axes.xaxis.set_minor_locator(mdates.MonthLocator(interval=1))

The plot will look like this...

Answered By - Redox