在python中删除tou-excel中的列名

Question

我想搜索数据帧中出现的特定单词。如果数据框中有word，则需要将dataframe的子集导出到Excel中。 这里的问题是每次调用列名称时。所有数据帧的列名相同。在

 df = pd.DataFrame({
    'Name': ['Ann', 'Juh', 'Jeo', 'Sam'],
    'Age': [43,29,42,59],
    'Task1': ['Drafting a letter', 'Sending', 'Pasting', 'Sending'],
    'Task2': ['Sending', 'Paking', 'Sending', 'Pasting'],
    'Task3': ['Packing', 'Letter Drafting', 'Paking', 'Letter Drafting']
    })

writer = pd.ExcelWriter("C:..\\pp.xlsx", engine='xlsxwriter')
row = 0
b = ['Sending','paking']
    for var in b: ----> # Here 'b' is searchable keywords.


        lower_df = df.apply(lambda x: x.astype(str).str.lower())

        margin = df[lower_df.iloc[:,3:5].astype(str).apply(lambda x: x.str.contains(var.lower())).any(axis=1)]


        margin['search_term'] = var   ---> #Create the column with search keyword 


        if len(margin) > 0: --->    #If no data found need to eliminate
            margin.to_excel(writer,startrow=row)
            row = row + len(margin.index) +1


    writer.save()

如果我使用header=False，它将删除所有的列名，但我希望保留dataframe的开头。在

Answer 1

您可以更改逻辑-将每个数据帧追加到列表dfs和最后一个^{}作为finalDataFrame：

writer = pd.ExcelWriter("pp.xlsx", engine='xlsxwriter')

b = ['Sending','paking']
dfs = []
for var in b: # Here 'b' is searchable keywords.

    lower_df = df.apply(lambda x: x.astype(str).str.lower())
    mask = (lower_df.iloc[:,3:5]
                    .astype(str)
                    .apply(lambda x: x.str.contains(var.lower()))
                    .any(axis=1))
    margin = df[mask].copy()

    margin['search_term'] = var   #Create the column with search keyword 
    #print (margin)

    dfs.append(margin)

pd.concat(dfs).to_excel(writer, index=False)
writer.save()