Pandas日常操作5个小技巧

Pandas日常操作5个小技巧

1、获取当前路径的绝对路径

dir_path = os.path.dirname(os.path.abspath(__file__))#获取当前路径的绝对路径filedirj = dir_path +'\\原始数据\\'#获取原始数据下文件绝对路径

2、设置千分位符

pf[pf.columns[11:558]] = pf[pf.columns[11:558]].applymap(lambdax:f'{x:,}')#改千分位格式,修改日期20230131

3、np查找字符串。np.char.find(x4['plmnIdList'],

x4['联通共享邻区']=np.where(np.char.find(x4['plmnIdList'],"mnc=01, mcc=460")>0,"是","否")#判断邻区为支持联通用户

4、Pandas列模糊筛选x4= x4[x4['plmnIdList'].str.contains(r'.*?mnc=01, mcc=460.*')]

x4= x4[x4['plmnIdList'].str.contains(r'.*?mnc=01, mcc=460.*')]#使用正则表达式进行模糊匹配,*匹瓯,判断邻区为支持联通用户

pf[nameclunm]=np.where(pf[nameclunm].astype(str).str.contains('\['),pf[nameclunm].str.replace("\[.+$","",regex=True),pf[nameclunm])

5、Pandas文本列联合操作

p_mo_cell['eci1'] = p_mo_cell['eNodeB标识'].astype(str) p_mo_cell['eci2'] = p_mo_cell['小区标识'].astype(str)print(p_mo_cell.dtypes) p_mo_cell['eci'] = p_mo_cell['eci1'].str.cat([p_mo_cell['eci2']],sep="-")