Pandas：使用循环和分层索引将多个csv文件导入dataframe

Question

Events 
1,0.32,0.20,0.67
2,0.94,0.19,0.14,0.21,0.94
3,0.32,0.20,0.64,0.32
4,0.87,0.13,0.61,0.54,0.25,0.43 
5,0.62,0.21,0.77,0.44,0.16

# get a list of all csv files in target directory
my_dir = "C:\\Data\\"
filelist = []
os.chdir( my_dir )
for files in glob.glob( "*.csv" ) :
    filelist.append(files)

# read each csv file into single dataframe and add a filename reference column 
# (i.e. file1, file2, file 3) for each file read
df = pd.DataFrame()
columns = range(1,100)
for c, f in enumerate(filelist) :
    key = "file%i" % c
    frame = pd.read_csv( (my_dir + f), skiprows = 1, index_col=0, names=columns )
    frame['key'] = key
    df = df.append(frame,ignore_index=True)

df1 = pd.DataFrame()
df2 = pd.DataFrame()
columns = range(1,100)
df1 = pd.read_csv("C:\\Data\\Currambene_001y09h00m_events.csv", 
                  skiprows = 1, index_col=0, names=columns)
df2 = pd.read_csv("C:\\Data\\Currambene_001y12h00m_events.csv", 
                  skiprows = 1, index_col=0, names=columns)
keys = [('file1'), ('file2')]
df = pd.concat([df1, df2], keys=keys, names=['fileno'])

我已经找到了许多相关的链接，但我仍然无法得到这个工作：

• 将多个CSV文件读取到Python Pandas DataFrame中
• 将多个不同列数的数据帧合并为一个大数据帧
• 将多个csv文件导入到pandas中并连接到一个Dataframe中

Answer 1

您需要决定要在什么轴上追加文件。熊猫总是试图通过以下方式做正确的事情：

1. 假设每个文件中的每一列都不同，如果需要，将数字附加到跨文件名称相似的列中，这样它们就不会混在一起；
2. 跨文件属于同一行索引的项并排放置在它们各自的列下。

有效追加的诀窍是将文件侧向倾斜，这样就可以获得与pandas.concat将执行的操作相匹配的所需行为。这是我的食谱：

from pandas import *
files = !ls *.csv # IPython magic
d = concat([read_csv(f, index_col=0, header=None, axis=1) for f in files], keys=files)

def reader(f):
    d = read_csv(f, index_col=0, header=None, axis=1)
    d.columns = range(d.shape[1])
    return d

df = concat([reader(f) for f in files], keys=files)