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#pip install pandas
#pip install lxml
#pip install openpyxl
# Importing pandas
import pandas as pd
# The webpage URL whose table we want to extract
url = "https://www.moneycontrol.com/mutual-funds/canara-robeco-blue-chip-equity-fund-direct-plan/portfolio-holdings/"
{
"code": 0,
"reason": "OK",
"result": [
{
"ctype": "news",
"dtype": 2,
"image": "https://img-staging.yana.asideas.de/image/fetch/w_1280,h_720,c_lfill,f_webp,g_auto:faces,q_auto:eco/https%3A%2F%2Fcdn.images.express.co.uk%2Fimg%2Fdynamic%2F78%2F750x445%2F1187631.jpg",
"imageUrl": [],
"docid": "xOUODFlNVun1vVnycPgLtg",
import json
import requests
with open("saijson.json", "r") as file:
json_data = json.loads(file)
json_s_data = json_data['result']
output_json = []
tmp_json = []
using namespace std;
using namespace boost;
enum class Color {red,green,blue};
enum class Size {large,medium, small};
struct Product{
#include <iostream>
#include <cstdio>
#include <string>
#include <vector>
#include <fstream>
#include <boost/lexical_cast.hpp>
using namespace std;
using namespace boost;
@venkatavamsy
venkatavamsy / .gitignore
Created September 29, 2018 19:18 — forked from octocat/.gitignore
Some common .gitignore configurations
# Compiled source #
###################
*.com
*.class
*.dll
*.exe
*.o
*.so
# Packages #
Summary
Overall risk level:
High
Risk ratings:
High:
1
Medium:
2
Low:
2
from pyelasticsearch import ElasticSearch
import pandas as pd
from time import time
root_path="<Root Path>"
raw_data_path=root_path+"data/"
csv_filename="predicted_data.csv"
t0=time()
@venkatavamsy
venkatavamsy / dabblet.css
Last active December 27, 2017 04:20
The first commented line is your dabblet’s title
/**
* The first commented line is your dabblet’s title
*/
background: #960;
min-height: 10%;
@venkatavamsy
venkatavamsy / Python_Image_OpenCV_line.py
Created March 22, 2017 07:46
Python Image OpenCV line
import cv2
import numpy as np
from matplotlib import pyplot as plt
img = cv2.imread('images.jpg',cv2.IMREAD_GRAYSCALE)
plt.imshow(img, cmap = 'gray', interpolation = 'bicubic')
plt.xticks([]), plt.yticks([]) # to hide tick values on X and Y axis
plt.plot([200,300,400],[100,200,300],'c', linewidth=5)
plt.show()