<jupyter_start><jupyter_text>importing the libraries<jupyter_code>import pandas as pd
import matplotlib.pyplot as plt 
#readint he data set


df = pd.read_csv("Monthly_data_cmo.csv")
a = df.head(51)
a
#remove columns

#syntax
#drop(labels, axis, index, columns, level, inplace, errors)

#for removing a simgle column :-
anomaly_free = a.drop(["state_name","arrivals_in_qtl","date"], axis=1)
anomaly_free
#dropping "state_name","arrivals_in_qtl","date"<jupyter_output><empty_output><jupyter_text>Dropping useless commodities<jupyter_code>anomaly_free_2 = anomaly_free.drop([8,9,10,11,12,13,14,15,16,17,24,26,27,28,36,42,43], axis=0)
anomaly_free_2<jupyter_output><empty_output><jupyter_text>having both 2015 and 2016 data of ahmednagar<jupyter_code>data15_16 = anomaly_free_2.sort_values('Year')
data15_16<jupyter_output><empty_output><jupyter_text>2016 data of ahmednagar<jupyter_code>data16 = data15_16.loc[data15_16['Year'] == 2016]
data16<jupyter_output><empty_output><jupyter_text>2015 data of ahmednagar<jupyter_code>data15 = data15_16.loc[data15_16['Year'] == 2015]
data15<jupyter_output><empty_output><jupyter_text>comparing the data of 2016 and 2015 with common vegetables  added the vegetables common in both the year<jupyter_code>com_data = pd.merge(data15,data16, on="Commodity")
com_data<jupyter_output><empty_output><jupyter_text>Getting the increase or decrease of minimum and maximum prices respectively<jupyter_code>com_data['min_price_dif'] = com_data['min_price_y'] - com_data['min_price_x']
com_data['max_price_dif'] = com_data['max_price_y'] - com_data['max_price_x']
com_data['modal_price_dif'] = com_data['modal_price_y'] - com_data['modal_price_x']
com_data<jupyter_output><empty_output><jupyter_text>Visualising the combined data set of 2015 and 2016 Ploting the graph showing the increase in minimum and maximum prices of common vegetables from 2015 to 2016 this graph represnts by how much the minimum price of vegetables is varying from year 2015 to 2016<jupyter_code>#plt.figure(figsize=(13,8))
plt.xticks(rotation=90)
plt.plot(com_data.Commodity, com_data.min_price_dif)
plt.plot(com_data.Commodity, com_data.max_price_dif)
#plt.plot(com_data.Commodity, com_data.max_price_dif)
plt.xlabel("Name",fontsize = 10)
plt.ylabel("increase or decrease",fontsize = 10)
plt.title("this graph represnts by how much the minimum and maximum price of vegetables is varying from year 2015 to 2016")
plt.legend(['min price','max price'],fontsize = 10)<jupyter_output><empty_output><jupyter_text>Ploting the graph showing the increase or decrease in modal prices of common vegetables from 2015 to 2016<jupyter_code>#plt.figure(figsize=(13,8))
plt.xticks(rotation=90)
plt.plot(com_data.Commodity, com_data.modal_price_dif)
plt.title("Ploting the graph showing by how much the increase or decrease in modal prices of common vegetables from 2015 to 2016",fontsize = 10)
plt.xlabel("Name",fontsize = 10)
plt.ylabel("increase or decrease",fontsize = 10)
plt.legend("modal_price",fontsize = 10)
plt.show()<jupyter_output><empty_output><jupyter_text>graph showing the minimum and maximum price of each commodity in both 2015 and 2016<jupyter_code>#plt.figure(figsize=(13,8))
plt.xticks(rotation=90)
plt.plot(com_data.Commodity,com_data.min_price_y,'o')
plt.plot(com_data.Commodity,com_data.min_price_x,'o')
plt.legend(['Min price in 2016','Min price in 2015'],fontsize = 10)
plt.xlabel("Name",fontsize = 10)
plt.ylabel("prices",fontsize = 10)
plt.title("graph showing the minimum price of each commodity in both 2015 and 2016",fontsize = 10)
plt.show()
com_data
#plt.figure(figsize=(13,8))
plt.xticks(rotation=90)
plt.plot(com_data.Commodity,com_data.max_price_y,'o')
plt.plot(com_data.Commodity,com_data.max_price_x,'o')
plt.legend(['max price in 2016','max price in 2015'],fontsize = 10)
plt.xlabel("Name",fontsize = 10)
plt.ylabel("prices",fontsize = 10)
plt.title("graph showing the maximum price of each commodity in both 2015 and 2016",fontsize = 10)
plt.show()<jupyter_output><empty_output><jupyter_text>Visualising the dataset of only 2016<jupyter_code>#printing out the dataset
data16<jupyter_output><empty_output><jupyter_text>ploting the graph showing the max price and min price of each commodity in 2016<jupyter_code>plt.figure(figsize=(16,5))
plt.plot(data16.Commodity,data16.min_price)
plt.plot(data16.Commodity,data16.max_price)
plt.xticks(rotation=90)
plt.legend(['min price in 2016','max price in 2016'],fontsize = 10)
plt.xlabel("Name",fontsize = 10)
plt.ylabel("prices",fontsize = 10)
plt.title("graph showing the max price and min price of each commodity in 2016",fontsize = 10)
plt.show()<jupyter_output><empty_output><jupyter_text>ploting the graph showing the modal price of each commodity in 2016<jupyter_code>plt.figure(figsize=(16,5))
plt.plot(data16.Commodity,data16.modal_price)
plt.xticks(rotation=90)
plt.legend(['modal price'],fontsize = 10)
plt.xlabel("Name",fontsize = 10)
plt.ylabel("prices",fontsize = 10)
plt.title("graph showing the modal price of each commodity in 2016",fontsize = 10)
plt.show()<jupyter_output><empty_output><jupyter_text>Visualising the dataset of only 2015<jupyter_code>#printing the data set

data15<jupyter_output><empty_output><jupyter_text>ploting the graph showing the max price and min price of each commodity in 2016<jupyter_code>#plt.figure(figsize=(13,8))
plt.xticks(rotation=90)
plt.plot(data15.Commodity,data15.min_price)
plt.plot(data15.Commodity,data15.max_price)
plt.legend(['min price in 2015','max price in 2015'],fontsize = 10)
plt.xlabel("Name",fontsize = 10)
plt.ylabel("prices",fontsize =10)
plt.title("graph showing the max price and min price of each commodity in 2015",fontsize = 10)
plt.show()<jupyter_output><empty_output><jupyter_text>ploting the graph showing the modal price of each commodity in 2015<jupyter_code>#plt.figure(figsize=(13,8))
plt.xticks(rotation=90)
plt.plot(data15.Commodity,data15.modal_price)
plt.legend(['modal price'],fontsize = 10)
plt.xlabel("Name",fontsize = 10)
plt.ylabel("prices",fontsize = 10)
plt.title("graph showing the modal price of each commodity in 2015",fontsize = 10)
plt.show()<jupyter_output><empty_output>
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