DataFrame.sort_values(by=‘進(jìn)行排序的列名或索引值', axis=0, ascending=True, inplace=False, kind=‘quicksort', na_position=‘last', ignore_index=False, key=None)

import pandas as pd
df = pd.read_csv('test.csv')
# 根據(jù)hello列降序排序
data = df.sort_values(by="hello", ascending=False, ,axis=0)
# axis=0表示按列，同理axis=1表示按行

import pandas as pd
df = pd.read_csv('test.csv')
# 根據(jù)第一列降序排序，當(dāng)?shù)谝涣邢嗤瑫r(shí)，根據(jù)第三列進(jìn)行升序排序。并且重置索引，替換原數(shù)據(jù)
data = df.sort_values(by = ['col1','col3'],ascending=[False,True],ignore_index=True,inplace=True)

# -*- coding: utf-8 -*-
# ---
# @Software: PyCharm
# @File: main.py
# @Author: WangYunchang
# @E-mail: wangyunchang@dxy.cn
# @Site: 
# @Time: 9月 20, 2022
# ---
import csv
import pandas as pd
import hashlib
counts = {}
# 讀取文件
txt = open("word2count.txt").read()
# 將大寫字母轉(zhuǎn)化為小寫
txt = txt.lower()
# 把文章中不是英文字母的全部代替為空格
for ch in '0123456789.,()%-':
    txt = txt.replace(ch, " ")
# 分割成列表
words = txt.split()
# 統(tǒng)計(jì)單詞
for word in words:
    counts[word] = counts.get(word, 0) + 1
items = list(counts.items())
# 將所得單詞及數(shù)目寫入csv文件中
csvFile = open('word_result.csv', 'w', newline='')
# 寫入表頭，A是單詞，B是出現(xiàn)次數(shù)
csv.writer(csvFile).writerow(["A", "MD5", "B"])
# 統(tǒng)計(jì)結(jié)果寫入csv
writer = csv.writer(csvFile)
for key in counts:
    # MD5值
    ss = hashlib.md5(key.encode('utf-8')).hexdigest()
    writer.writerow([key, ss, counts[key]])
csvFile.close()
df = pd.read_csv('word_result.csv')
# 根據(jù)B降序排序，當(dāng)B相同時(shí)，根據(jù)MD5進(jìn)行降序排序
data = df.sort_values(by=["B", "MD5"], ascending=[False, False])
# 刪除MD5
data = data.drop(columns="MD5")
# 把新的數(shù)據(jù)寫入文件
data.to_csv('word_result.csv', mode='w', index=False)