Pyplot subplot title3/25/2023 ![]() ![]() The following is the code that I have used for creating the subplots. The output DataFrame is embedded in the following picture.įigure 2 - Intemediate DataFrame Creating Subplots The purpose of the above code is to create another DataFrame that will hold the names of states, their weights, and the latest inflation number for the month of Jan 2023. #importing libraries import pandas as pd import os import numpy as np import matplotlib.pyplot as plt %matplotlib inline #setting ploting style ('fivethirtyeight') color_pal=_key() #changing dir os.chdir("path of the working dir") #working dir print(os.getcwd()) #naming file file ="2022_05_18_State_CPI_Index.xlsx" #loading file from disc df= pd.read_excel(file) #extracting names of all states form the dataframe states = df.drop_duplicates() #extracting all the weights for combined index from the dataframe weights = df.drop_duplicates() #extracting values of latest combined inflation from dataframe comb_infla = df.query("Date = ''") #combining all the three values in one single dataframe df1 = pd.concat(,axis=1) #sorting the dataframe by "Comined Weights" df1 = df1.sort_values(by=, axis=0, ascending=False) #resets the values of row index of df1 df1.reset_index(drop=True, inplace = True) #droping the first value which is "Pan India" df1 = df1 #storing the values of states in a list for iterating states = df1 In this article, I have explained how to add title to plots using pandas here, I have added the title to the histogram plots and bar graphs using title keyword.The following is the code that we can use to process this data for the purpose of feeding into the plotting module. Pandas bar chart with xlabel, ylabel, and title, applied using Matplotlib pyplot interface. title : Using this we can set the title of bars.ylabel : It is used for set the label of y axis.xlabel : It is used for set the label of x axis.In Pandas plot(), labeling of the axis is done by using the Matplotlib syntax on the “plt” object imported from pyplot. ![]() If we give labeling of the x and y axis and set the title in a bar graph, it will give a better understanding to us. For that, we need to create Pandas DataFrame using Python Dictionary. ![]() Use Pandas plot() function we can plot multiple variables of DataFrame.Ĭreate a histogram using the pandas hist() method, which is a default method. It provides several different functions to visualizing our data with the help of the plot() function. When we want to create exploratory data analysis plots, we can use Pandas is highly useful and practical. In Python Pandas library is mainly focused for data analysis and it is not only a data visualization library but also using this we can create a basic plots. # Example 3: Get the individual column as a barĭf.plot(kind="bar", title="test") # Example 2: Create title of individual columns of histogramĭf.plot(kind='hist', subplots=True, title=) Df.plot(kind = 'hist', title = 'Students Marks')
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