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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Finally able to do Reverse Geocoding without using any paid API
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Lets try selecting rows from a DataFrame with indexes
Step1:  So we had to just put the parentheses
Step2:  Time taken to execute a cell
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Python Code:
import numpy as np
import pandas as pd
# importing the dataset we prepared and saved using Baseline 1 Notebook
ricep = pd.read_csv("/Users/macbook/Documents/BTP/Notebook/BTP/ricep.csv")
ricep.head()
ricep = ricep.drop(["Unnamed: 0"],axis=1)
ricep["phosphorus"] = ricep["phosphorus"]*10
ricep["value"] = ricep["Production"]/ricep["Area"]
ricep.head()
ricep.index[ ricep['ind_district'] == 'anantapur'].tolist()
ricep.index[ ricep['ind_district'] == 'anantapur' & ricep['Crop_Year'] == '2002' ]
ricep.index[ (ricep['ind_district'] == 'anantapur') & (ricep['Crop_Year'] == 2002) ].tolist()
Explanation: Finally able to do Reverse Geocoding without using any paid API
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Lets try selecting rows from a DataFrame with indexes
End of explanation
a = np.empty((ricep.shape[0],1))*np.NAN
ricex = ricep.assign(test = a)
ricex.head()
Explanation: So we had to just put the parentheses
End of explanation
%time
v = ricex.iloc[0,13]
v
d = v + 5
d
if pd.isnull(v):
    v = 3
v+5
v
df = pd.DataFrame(np.arange(1,7).reshape(2,3),
                  columns = list('abc'), 
                  index=pd.Series([2,5], name='b'))
df
x = 3
x += 2
x
s = "Akshansh"
s[-4]
# bx = False
# if bx: continue
# else: bx = True
Explanation: Time taken to execute a cell
End of explanation
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