python 逐行读取 yelp 数据集
read from line to line yelp dataset by python
我想把这段代码改成专门从1400001行读到1450000行。什么是修改?
文件由单一对象类型组成,每行一个 JSON-object。
我还想将输出保存到 .csv 文件。我该怎么办?
revu=[]
with open("review.json", 'r',encoding="utf8") as f:
for line in f:
revu = json.loads(line[1400001:1450000)
如果每行 JSON:
revu=[]
with open("review.json", 'r',encoding="utf8") as f:
# expensive statement, depending on your filesize this might
# let you run out of memory
revu = [json.loads(s) for s in f.readlines()[1400001:1450000]]
如果你在 /etc/passwd 文件上做它很容易测试(当然没有 json,所以被遗漏了)
revu = []
with open("/etc/passwd", 'r') as f:
# expensive statement
revu = [s for s in f.readlines()[5:10]]
print(revu) # gives entry 5 to 10
或者您遍历所有行,避免内存问题:
revu = []
with open("...", 'r') as f:
for i, line in enumerate(f):
if i >= 1400001 and i <= 1450000:
revu.append(json.loads(line))
# process revu
到 CSV ...
import pandas as pd
import json
def mylines(filename, _from, _to):
with open(filename, encoding="utf8") as f:
for i, line in enumerate(f):
if i >= _from and i <= _to:
yield json.loads(line)
df = pd.DataFrame([r for r in mylines("review.json", 1400001, 1450000)])
df.to_csv("/tmp/whatever.csv")
我想把这段代码改成专门从1400001行读到1450000行。什么是修改? 文件由单一对象类型组成,每行一个 JSON-object。 我还想将输出保存到 .csv 文件。我该怎么办?
revu=[]
with open("review.json", 'r',encoding="utf8") as f:
for line in f:
revu = json.loads(line[1400001:1450000)
如果每行 JSON:
revu=[]
with open("review.json", 'r',encoding="utf8") as f:
# expensive statement, depending on your filesize this might
# let you run out of memory
revu = [json.loads(s) for s in f.readlines()[1400001:1450000]]
如果你在 /etc/passwd 文件上做它很容易测试(当然没有 json,所以被遗漏了)
revu = []
with open("/etc/passwd", 'r') as f:
# expensive statement
revu = [s for s in f.readlines()[5:10]]
print(revu) # gives entry 5 to 10
或者您遍历所有行,避免内存问题:
revu = []
with open("...", 'r') as f:
for i, line in enumerate(f):
if i >= 1400001 and i <= 1450000:
revu.append(json.loads(line))
# process revu
到 CSV ...
import pandas as pd
import json
def mylines(filename, _from, _to):
with open(filename, encoding="utf8") as f:
for i, line in enumerate(f):
if i >= _from and i <= _to:
yield json.loads(line)
df = pd.DataFrame([r for r in mylines("review.json", 1400001, 1450000)])
df.to_csv("/tmp/whatever.csv")