Question

是否可以使用pandas从工作表excel文件中读取多个表？就像是：从row0读取table1直到row100 从第102行读取table2直到第202行 ...

Answer 1

假设我们有以下Excel文件：

解决方案：我们正在解析第一张表（索引：0）

xl = pd.ExcelFile(fn)
nrows = xl.book.sheet_by_index(0).nrows

df1 = xl.parse(0, skipfooter= nrows-(10+1)).dropna(axis=1, how='all')
df2 = xl.parse(0, skiprows=12).dropna(axis=1, how='all')

编辑：skip_footer已替换为skipfooter

<强>结果：

In [123]: df1
Out[123]:
    a   b   c
0  78  68  33
1  62  26  30
2  99  35  13
3  73  97   4
4  85   7  53
5  80  20  95
6  40  52  96
7  36  23  76
8  96  73  37
9  39  35  24

In [124]: df2
Out[124]:
   c1  c2  c3 c4
0  78  88  59  a
1  82   4  64  a
2  35   9  78  b
3   0  11  23  b
4  61  53  29  b
5  51  36  72  c
6  59  36  45  c
7   7  64   8  c
8   1  83  46  d
9  30  47  84  d

Answer 2

首先阅读整个csv文件：

import pandas as pd
df = pd.read_csv('path_to\\your_data.csv')

然后获取各个帧，例如使用：

df1 = df.iloc[:100,:]
df2 = df.iloc[100:200,:]

Answer 3

我编写了以下代码来自动识别多个表，以防万一您需要处理许多文件并且不想查看每个文件以获取正确的行号。该代码还将在每个表上方查找非空行，并将其作为表元数据读取。

def parse_excel_sheet(file, sheet_name=0, threshold=5):
    '''parses multiple tables from an excel sheet into multiple data frame objects. Returns [dfs, df_mds], where dfs is a list of data frames and df_mds their potential associated metadata'''
    xl = pd.ExcelFile(file)
    entire_sheet = xl.parse(sheet_name=sheet_name)

    # count the number of non-Nan cells in each row and then the change in that number between adjacent rows
    n_values = np.logical_not(entire_sheet.isnull()).sum(axis=1)
    n_values_deltas = n_values[1:] - n_values[:-1].values

    # define the beginnings and ends of tables using delta in n_values
    table_beginnings = n_values_deltas > threshold
    table_beginnings = table_beginnings[table_beginnings].index
    table_endings = n_values_deltas < -threshold
    table_endings = table_endings[table_endings].index
    if len(table_beginnings) < len(table_endings) or len(table_beginnings) > len(table_endings)+1:
        raise BaseException('Could not detect equal number of beginnings and ends')

    # look for metadata before the beginnings of tables
    md_beginnings = []
    for start in table_beginnings:
        md_start = n_values.iloc[:start][n_values==0].index[-1] + 1
        md_beginnings.append(md_start)

    # make data frames
    dfs = []
    df_mds = []
    for ind in range(len(table_beginnings)):
        start = table_beginnings[ind]+1
        if ind < len(table_endings):
            stop = table_endings[ind]
        else:
            stop = entire_sheet.shape[0]
        df = xl.parse(sheet_name=sheet_name, skiprows=start, nrows=stop-start)
        dfs.append(df)

        md = xl.parse(sheet_name=sheet_name, skiprows=md_beginnings[ind], nrows=start-md_beginnings[ind]-1).dropna(axis=1)
        df_mds.append(md)
    return dfs, df_mds

pandas read_excel在同一张纸上的多个表

3 个答案: