excelFile = r'analyze_search_category.xlsx' df = pd.DataFrame(pd.read_excel(excelFile)) print(df)
详情:(21条消息) 在Python中使用Pandas.DataFrame对Excel操作笔记一 - 从Excel里面获取说需要的信息_fengqiaoxian的博客-CSDN博客_dataframe读取excel
df_exposure = pd.read_csv('haah.txt', sep='\t', header=None) # df_exposure.columns = ['y%s'%i for i in range(1, df_exposure.shape[1]+1)] df_exposure.columns=['qq','ss1','ss2','ss3','ss4','aa']
上述.txt文件在代码同一目录,所以不用写路径。
#定义导出的路径,并定义好文件名
resultPath = 'D:\我的文件\桌面内容\使用python读取Excel的路径\表格3.xlsx'
#导出文件
df3.to_excel(resultPath,sheet_name = "汇总",index = False,na_rep = 0,inf_rep = 0)
如何将python处理好的DataFrame格式数据导出为xlsx格式的Excel文件? - 知乎 (zhihu.com)
【Python】DataFrame输出为csv\txt\xlsx文件_J小白Y的博客-CSDN博客_python dataframe输出csv文件 出现中文乱码:
# df转化为csv格式 resultPath = 'D:\pycharmproject\search_category\search_category2_3.csv' #导出文件 df_search.to_csv(resultPath,sep=',',index=False,header=False,encoding='utf_8_sig') #index是否要索引,header是否要列名,True就是需要
#清空文件 file = open('search_category2_dic.txt', 'w').close() #把字典转为文本search_category2_dic file = open('search_category2_dic.txt', 'w',encoding='utf-8') for k,v in datadict.items(): file.write(str(k)+' '+str(v)+'\n') file.close()
(22条消息) Python pandas 将Dataframe转化为列表嵌套字典_不知道怎么写代码的麻瓜的博客-CSDN博客_python将dataframe转为字典
(24条消息) 自定义一种pandas转化为python字典类型的形式_卡卡卡骨的博客-CSDN博客_python pandas 转字典
list1 = ["a", "b", "c", "d"]
print(",".join(list1))结果:
a,b,c,d
open_diff = open(' XX.txt','r',encoding='utf-8') # 源文本文件
diff_line = open_diff.readlines()
line_list = []
for line in diff_line:
line_list.append(line)
count = len(line_list)
print('源文件数据行数:',count)
#切分diff
diff_match_split = [line_list[i:i+50000] for i in range(0,len(line_list),50000)]# 每个文件的数据行数
for i,j in zip(range(0,int(count/50000+1)),range(0,int(count/50000+1))): # 写入txt,计算需要写入的文件数
with open('./dataText/data%s.txt'%j,'w+',encoding='utf-8') as temp:
for line in diff_match_split[i]:
temp.write(line)
print('拆分后文件个数:',i+1)
多个csv读取成一个
import pandas as pd
import glob
# dataCsv/data0.csv
csv_list = glob.glob(r'dataCsv/*.csv')
len(csv_list)
for i in csv_list:
fr = open(i,'rb').read()
with open('search_title_all_click.csv','ab') as f:
f.write(fr)