Question

我有csv文件，其内容如下：

a       b
ca  12, 20, 45
ca  18, 27
ca  30, 32, 41, 49
ny  4, 12, 12, 37, 43
ny  33
ny  8, 10, 40, 44

如何将数据读入python作为pandas DataFrame并获取每行的均值和总和值？

求和示例

Answer 1

这并不容易，因为没有结构良好的csv指向BrenBarn。

解决方案：

主要问题是您不知道列数，需要添加到read_csv中的参数names以避免error，因此您必须使用某些常量，例如N = 20 ：

CParserError：标记数据时出错。 C错误：第4行预计4个字段，见5

import pandas as pd
from pandas.compat import StringIO

temp=u""" a    b
ca  12, 20, 45
ca  18, 27
ca  30, 32, 41, 49
ny  4, 12, 12, 37, 43
ny  33
ny  8, 10, 40, 44
"""
#after testing replace 'StringIO(temp)' to 'filename.csv'
N = 20
df = pd.read_csv(StringIO(temp), sep="\s+", names = range(N), skiprows = 1)
#print (df)

#create index from first column, remove all NaN columns, cast to str
df = df.set_index(0).rename_axis('a').dropna(axis=1, how='all').astype(str)
#remove all , and spaces, cast to float
df = df.apply(lambda x: x.str.strip(' ,')).astype(float)
#sum and if necessary cast to int
df1 = df.sum(axis=1).astype(int).rename('b').reset_index()
print (df1)
    a    b
0  ca   77
1  ca   45
2  ca  152
3  ny  108
4  ny   33
5  ny  102

#if need spaces
mask = df1.a != df1.a.shift()
df1.a = df1.a.where(mask,'')

print (df1)
    a    b
0  ca   77
1       45
2      152
3  ny  108
4       33
5      102

更动态的解决方案：

#get max count of space separators
data = []
with open('file.csv') as f:
    lines = f.readlines()
    for line in lines:
        data.append(len(line.split()))

#if necessary add 1
N = max(data)
print (N)
6

df = pd.read_csv('file.csv', sep="\s+",  skiprows = 1, names = range(N))
print (df)
    0    1    2    3    4     5
0  ca  12,  20,   45  NaN   NaN
1  ca  18,   27  NaN  NaN   NaN
2  ca  30,  32,  41,   49   NaN
3  ny   4,  12,  12,  37,  43.0
4  ny   33  NaN  NaN  NaN   NaN
5  ny   8,  10,  40,   44   NaN

Answer 2

设置

import pandas as pd
from pandas.compat import StringIO

txt = """a       b
ca  12, 20, 45
ca  18, 27
ca  30, 32, 41, 49
ny  4, 12, 12, 37, 43
ny  33
ny  8, 10, 40, 44"""

<强> 溶液
使用\s{2,}分隔符读取文件，该分隔符指定两个或多个空格。这将分为a和b列。然后我们可以事后处理b。

df = pd.read_csv(StringIO(txt), sep='\s{2,}', engine='python', index_col=0)
df = df.b.str.split(',\s*', expand=True).astype(float) \
       .sum(1).astype(int).to_frame(name='b')

print(df)

      b
a      
ca   77
ca   45
ca  152
ny  108
ny   33
ny  102

pandas DataFrame中不均匀大小的列的总和

2 个答案: