How to reindex, reformat years in graph
Question:
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()
Answers:
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…
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()
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…