我有一个excel文件,我需要从某个工作表的行中提取某些数据。到目前为止我已经
了import pandas as pd
xl_file = pd.ExcelFile((xlfilePath)
dfs = {sheet_name: xl_file.parse(sheet_name) for sheet_name in xl_file.sheet_names}
现在我想读一下特定行中的数值。行结构类似于:
Length (mm) 10.1 - 16.0 - 19.5 - 16.4 - 11.3
我试图显示行的每个单元格中的内容。破折号表示单元格中的空条目!如何使用pandas库读取这样的行?我碰巧知道上面一行有哪些行号,但是pandas有没有办法查看数据框并查找条目length (mm)
而不必指定行号?
编辑:EdChum建议的实际df.loc ['length(mm)']如下所示:
0 17.92377
Unnamed: 1 NaN
0.05 18.55764
Unnamed: 3 NaN
0.1 19.17039
Unnamed: 5 NaN
0.15 19.7507
Unnamed: 7 NaN
0.2 20.29776
Unnamed: 9 NaN
0.25 20.80492
Unnamed: 11 NaN
0.3 21.2667
Unnamed: 13 NaN
0.35 21.67687
Unnamed: 15 NaN
0.4 22.02884
Unnamed: 17 NaN
0.45 22.3156
Unnamed: 19 NaN
0.5 22.53051
Unnamed: 21 NaN
0.55 22.66691
Unnamed: 23 NaN
0.6 22.71949
Unnamed: 25 NaN
0.65 22.68477
Unnamed: 27 NaN
0.7 22.56162
Unnamed: 29 NaN
0.75 22.35258
Unnamed: 31 NaN
0.8 22.06432
Unnamed: 33 NaN
0.85 21.7079
Unnamed: 35 NaN
0.9 21.29801
Unnamed: 37 NaN
0.95 20.85419
Unnamed: 39 NaN
1 20.394
Name: length (mm), dtype: object
答案 0 :(得分:1)
加载df后,您可以使用标签索引loc
选择特定行:
df.loc['length (mm)']
如果你想要一个np.array,请执行:
df.loc['length (mm)'].values
答案 1 :(得分:0)
在读取文件时,您始终可以以数据框参数的形式指定列名。
import pandas as pd
fields = ['employee_name']
d_frame = pd.read_csv('data_file.csv', skipinitialspace=True, usecols=fields)
# get the required key or column name
print d_frame.keys()
# Get data from column name
print d_frame.employee_name
我认为employee_name
将是您要从中获取值的列名。