基础向-Pandas数据分析的常用操作（1）

获取和了解数据

导入必要的库

import pandas as pd
import numpy as np
import json

创建随机数字构成的DataFrame

data = '{"\\u6b3e\\u53f7\\u7f16\\u7801":{"0":11059080069,"1":11059080070,"2":11059080070,"3":11059080071,"4":11059080071,"5":11059080071,"6":11059081050,"7":11059081050,"8":11059081052,"9":11059200049,"10":11059200130,"11":11059230015,"12":11059240017,"13":11059240022,"14":11059240034,"15":11059240108,"16":11059240108,"17":11059240118,"18":11059240118,"19":11059240120,"20":11059240120,"21":11059240127,"22":11059240127,"23":11059241002,"24":11059241002,"25":11059241003,"26":11059241003,"27":11059241015,"28":11059241015,"29":11059241022,"30":11059241023,"31":11059241031,"32":11059241031,"33":11059241038,"34":11059241038,"35":11059241067,"36":11059241079,"37":11059241098,"38":11059241098,"39":11059241103,"40":11059241103},"\\u8272\\u53f7\\u7f16\\u7801":{"0":800,"1":3445,"2":7480,"3":870,"4":3445,"5":7480,"6":3430,"7":9000,"8":820,"9":850,"10":890,"11":840,"12":840,"13":810,"14":840,"15":840,"16":1100,"17":840,"18":870,"19":820,"20":870,"21":840,"22":890,"23":830,"24":890,"25":820,"26":870,"27":822,"28":830,"29":820,"30":840,"31":820,"32":822,"33":850,"34":870,"35":850,"36":840,"37":840,"38":870,"39":820,"40":870},"\\u6700\\u65e9\\u5230\\u5e97\\u65e5\\u671f":{"0":20190819,"1":20190819,"2":20190819,"3":20190708,"4":20190708,"5":20190708,"6":20190708,"7":20190708,"8":20190819,"9":20190619,"10":20190619,"11":20190619,"12":20190708,"13":20190619,"14":20190708,"15":20190813,"16":20190813,"17":20190723,"18":20190723,"19":20190708,"20":20190708,"21":20190813,"22":20190813,"23":20190723,"24":20190723,"25":20190723,"26":20190723,"27":20190708,"28":20190708,"29":20190813,"30":20190708,"31":20190624,"32":20190624,"33":20190723,"34":20190723,"35":20190723,"36":20190813,"37":20170101,"38":20190708,"39":20190813,"40":20190813},"\\u5728\\u624b\\u5e93\\u5b58":{"0":15,"1":16,"2":14,"3":16,"4":17,"5":13,"6":17,"7":18,"8":18,"9":15,"10":0,"11":23,"12":26,"13":0,"14":24,"15":23,"16":24,"17":18,"18":15,"19":9,"20":26,"21":24,"22":24,"23":33,"24":18,"25":28,"26":29,"27":21,"28":28,"29":27,"30":40,"31":0,"32":19,"33":28,"34":28,"35":31,"36":27,"37":0,"38":25,"39":29,"40":27},"\\u5728\\u624b\\u6b3e\\u8272\\u6570":{"0":1,"1":1,"2":1,"3":1,"4":1,"5":1,"6":1,"7":1,"8":1,"9":1,"10":0,"11":1,"12":1,"13":0,"14":1,"15":1,"16":1,"17":1,"18":1,"19":1,"20":1,"21":1,"22":1,"23":1,"24":1,"25":1,"26":1,"27":1,"28":1,"29":1,"30":1,"31":0,"32":1,"33":1,"34":1,"35":1,"36":1,"37":0,"38":1,"39":1,"40":1},"14\\u5929\\u52a8\\u9500\\u6b3e\\u8272\\u6570":{"0":1.0,"1":1.0,"2":1.0,"3":null,"4":0.0,"5":1.0,"6":1.0,"7":0.0,"8":null,"9":1.0,"10":0.0,"11":1.0,"12":1.0,"13":0.0,"14":0.0,"15":1.0,"16":0.0,"17":1.0,"18":1.0,"19":1.0,"20":0.0,"21":0.0,"22":1.0,"23":1.0,"24":1.0,"25":1.0,"26":1.0,"27":1.0,"28":1.0,"29":1.0,"30":1.0,"31":0.0,"32":1.0,"33":null,"34":null,"35":1.0,"36":1.0,"37":0.0,"38":1.0,"39":1.0,"40":1.0},"14\\u5929\\u96f6\\u552e\\u91cf":{"0":1.0,"1":1.0,"2":2.0,"3":null,"4":0.0,"5":3.0,"6":1.0,"7":0.0,"8":null,"9":2.0,"10":0.0,"11":1.0,"12":2.0,"13":0.0,"14":0.0,"15":1.0,"16":0.0,"17":3.0,"18":7.0,"19":7.0,"20":0.0,"21":0.0,"22":1.0,"23":9.0,"24":6.0,"25":8.0,"26":1.0,"27":1.0,"28":1.0,"29":4.0,"30":3.0,"31":1.0,"32":4.0,"33":null,"34":null,"35":1.0,"36":1.0,"37":null,"38":1.0,"39":1.0,"40":1.0},"\\u96f6\\u552e\\u91d1\\u989d\\uff0814\\u5929\\uff09":{"0":"179.5","1":"242.2","2":"391.7","3":null,"4":"0","5":"647.5","6":"242.2","7":"0","8":null,"9":"257.6","10":"0","11":"125","12":"199","13":"0","14":"0","15":"193.6","16":"0","17":"493","18":"1,114.80","19":"1,139.50","20":"0","21":"0","22":"193.6","23":"1,874.70","24":"1,106.60","25":"1,320.80","26":"199","27":"145","28":"145","29":"682.6","30":"521.4","31":"199","32":"714.8","33":null,"34":null,"35":"274.6","36":"177.4","37":null,"38":"193.6","39":"177.4","40":"177.4"}}'

init_data = pd.read_json(data)

浏览前10行数据

款号编码 色号编码 最早到店日期 在手库存 在手款色数 14天动销款色数 14天零售量 零售金额（14天）
0 11059080069 800 20190819 15 1 1.0 1.0 179.5
1 11059080070 3445 20190819 16 1 1.0 1.0 242.2
2 11059080070 7480 20190819 14 1 1.0 2.0 391.7
3 11059080071 870 20190708 16 1 NaN NaN None
4 11059080071 3445 20190708 17 1 0.0 0.0 0
5 11059080071 7480 20190708 13 1 1.0 3.0 647.5
6 11059081050 3430 20190708 17 1 1.0 1.0 242.2
7 11059081050 9000 20190708 18 1 0.0 0.0 0
8 11059081052 820 20190819 18 1 NaN NaN None
9 11059200049 850 20190619 15 1 1.0 2.0 257.6

init_data.head(10)

DataFrame有多少行？

init_data.shape[0]

41

DataFrame有多少列？

init_data.shape[1]

8

输出DataFrame所有列名

init_data.columns.values.tolist()

[‘款号编码’, ‘色号编码’, ‘最早到店日期’, ‘在手库存’, ‘在手款色数’, ‘14天动销款色数’, ‘14天零售量’, ‘零售金额（14天）’]

DataFrame的索引构成是什么样子的？

init_data.index

Int64Index([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,
34, 35, 36, 37, 38, 39, 40],
dtype=‘int64’)

14天最大的零售量列是多少？

init_data['14天零售量'].max()

9.0

哪个款卖的最好？

方法1

init_data['零售金额（14天）'] = init_data['零售金额（14天）'].apply(lambda x:float(str(x).replace(',','')) if x != None else 0)
sale = init_data.groupby(['款号编码'])['零售金额（14天）'].sum().reset_index()
sale.sort_values(by=['零售金额（14天）'],ascending=False,inplace=True)
sale = sale.reset_index(drop=True)
sale['款号编码'][0]

11059241002

方法2

init_data['零售金额（14天）'] = init_data['零售金额（14天）'].apply(lambda x:float(str(x).replace(',','')) if x != None else 0)
init_data.loc[init_data['零售金额（14天）'] == init_data['零售金额（14天）'].max(),'款号编码'].tolist()[0]

11059241002

总零售金额是多少？

init_data['零售金额（14天）'].sum()

13328.5

DataFrame里一共有多少款？

init_data['款号编码'].nunique()

26

平均每个款有几个色？

init_data['款色'] = init_data['款号编码'] + init_data['色号编码']
init_data['款色'].nunique() / init_data['款号编码'].nunique()

1.5769230769230769

本文地址：https://blog.csdn.net/A_010001001110/article/details/107137299