Python使用pandas将表格数据进行处理

# 创建physical_examination索引
PUT /physical_examination
{
  "settings": {
    "index": {
      "number_of_shards": "1",
      "number_of_replicas": "1"
    }
  },
  "mappings": {
    "properties": {
      "nums": {
        "type": "integer"
      },
      "name": {
        "type": "text"
      },
      "sex": {
        "type": "text"
      },
      "phone": {
        "type": "integer"
      },
      "result": {
        "type": "text"
      }
    }
  }
}

# 向physical_examination索引中添加数据
POST physical_examination/_bulk
{"index":{"_id":"1"}}
{"nums":1,"name":"刘一","sex":"男","phone":1234567891,"result":"优秀"}
{"index":{"_id":"2"}}
{"nums":2,"name":"陈二","sex":"男","phone":1234567892,"result":"优秀"}
{"index":{"_id":"3"}}
{"nums":3,"name":"张三","sex":"男","phone":1234567893,"result":"优秀"}
{"index":{"_id":"4"}}
{"nums":4,"name":"李四","sex":"男","phone":1234567894,"result":"优秀"}
{"index":{"_id":"5"}}
{"nums":5,"name":"王五","sex":"男","phone":1234567895,"result":"优秀"}

# 查询索引中的所有数据
GET physical_examination/_search
{
  "query": {
    "match_all": {}
  }
}

# 读取json中体检信息
with open('./data/physical_examination.json', 'r', encoding='utf-8') as f:
    data_json = f.read()
print(data_json)
 
# 处理json数据中的异常数据
if 'false' in data_json:
    data_json = data_json.replace('false', "False")
 
data_json = eval(data_json)
print(data_json)
 
print(data_json['hits']['hits'])
print('*' * 100)
 
valid_data = data_json['hits']['hits']
need_data = []
for data in valid_data:
    print(data['_source'])
    need_data.append(data['_source'])
print(need_data)

# 读取需要填补数据的表格
data_xlsx = pd.read_excel('./data/体检表.xlsx', sheet_name='Sheet1')
# print(data_xlsx)
 
# 获取excel表格的行列
row, col = data_xlsx.shape
print(row, col)
 
# 修改表格中的数据
for i in range(row):
    bb = data_xlsx.iloc[i]
    print(bb['姓名'], bb['手机号'])
    if pd.isnull(bb['手机号']):
        bb['手机号'] = '666'
        for cc in need_data:
            if cc['name'] == bb['姓名']:
                bb['手机号'] = cc['phone']
            data_xlsx.iloc[i, 3] = bb['手机号']
    print(bb['姓名'], bb['手机号'])
    print("-" * 100)
print(data_xlsx)

# 保存数据到新文件中
data_xlsx.to_excel('./data/new_data.xlsx', sheet_name='Sheet1', index=False, header=True)

import pandas as pd
 
# 读取json中体检信息
with open('./data/physical_examination.json', 'r', encoding='utf-8') as f:
    data_json = f.read()
print(data_json)
 
# 处理json数据中的异常数据
if 'false' in data_json:
    data_json = data_json.replace('false', "False")
 
data_json = eval(data_json)
print(data_json)
 
print(data_json['hits']['hits'])
print('*' * 100)
 
valid_data = data_json['hits']['hits']
need_data = []
for data in valid_data:
    print(data['_source'])
    need_data.append(data['_source'])
print(need_data)
 
# 读取需要填补数据的表格
data_xlsx = pd.read_excel('./data/体检表.xlsx', sheet_name='Sheet1')
# print(data_xlsx)
 
# 获取excel表格的行列
row, col = data_xlsx.shape
print(row, col)
 
# 修改表格中的数据
for i in range(row):
    bb = data_xlsx.iloc[i]
    print(bb['姓名'], bb['手机号'])
    if pd.isnull(bb['手机号']):
        bb['手机号'] = '666'
        for cc in need_data:
            if cc['name'] == bb['姓名']:
                bb['手机号'] = cc['phone']
            data_xlsx.iloc[i, 3] = bb['手机号']
    print(bb['姓名'], bb['手机号'])
    print("-" * 100)
print(data_xlsx)
 
# 保存数据到新文件中
data_xlsx.to_excel('./data/new_data.xlsx', sheet_name='Sheet1', index=False, header=True)