Home  >  Article  >  Backend Development  >  Data analysis using python

Data analysis using python

怪我咯
怪我咯Original
2017-04-08 10:54:591604browse

1: How to parse data in json format

import json,os,sys
current_dir=os.path.abspath(".")

filename=[file for file in os.listdir(current_dir) if ".txt" in file]#得到当前目录中,后缀为.txt的数据文件
fn=filename[0] if len(filename)==1 else "" #从list中取出第一个文件名

if fn: # means we got a valid filename
  fd=open(fn)
  content=[json.loads(line) for line in fd]
  
else:
  print("no txt file in current directory")
  sys.exit(1)
for linedict in content:
  for key,value in linedict.items():
    print(key,value)
  print("\n")


2: Occurrence frequency statistics

import random
from collections import Counter
fruits=[random.choice(["apple","cherry","orange","pear","watermelon","banana"]) for i in range(20)]
print(fruits) #查看所有水果出现的次数

cover_fruits=Counter(fruits)
for fruit,times in cover_fruits.most_common(3):
  print(fruit,times)

########运行结果如下:apple在fruits里出了5次
apple 5  
banana 4
pear 4


3: Method of reloading module py3

import importlib
import.reload(modulename)


4: Which modules are included in pylab

from pylab import *

is equivalent to the following import statement:

from pylab import *
  from numpy import *
  from scipy import *
  import matplotlib

The above is the detailed content of Data analysis using python. For more information, please follow other related articles on the PHP Chinese website!

Statement:
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn