Pandas:连接文件但跳过第一个文件以外的标题 [英] Pandas: Concatenate files but skip the headers except the first file

问题描述

我有 3 个文件，表示相同的数据集分成 3 个，我需要连接:

I have 3 files representing the same dataset split in 3 and I need to concatenate:

import pandas

df1 = pandas.read_csv('path1')
df2 = pandas.read_csv('path2')
df3 = pandas.read_csv('path3')

df = pandas.concat([df1,df2,df3])

但这会将标题保留在数据集的中间，我需要从第二个和第三个文件中删除标题(列名).我该怎么做?

But this will keep the headers in the middle of the dataset, I need to remove the headers (column names) from the 2nd and 3rd file. How do I do that?

推荐答案

我认为你需要 numpy.concatenate 和 DataFrame 构造函数:

I think you need numpy.concatenate with DataFrame constructor:

df = pd.DataFrame(np.concatenate([df1.values, df2.values, df3.values]), columns=df1.columns)

另一种解决方案是替换 df2 和 df3 中的列名:

Another solution is replace columns names in df2 and df3:

df2.columns = df1.columns
df3.columns = df1.columns
df = pd.concat([df1,df2,df3], ignore_index=True)

示例:

np.random.seed(100)
df1 = pd.DataFrame(np.random.randint(10, size=(2,3)), columns=list('ABF'))
print (df1)
   A  B  F
0  8  8  3
1  7  7  0

df2 = pd.DataFrame(np.random.randint(10, size=(1,3)), columns=list('ERT'))
print (df2)
   E  R  T
0  4  2  5

df3 = pd.DataFrame(np.random.randint(10, size=(3,3)), columns=list('HTR'))
print (df3)
   H  T  R
0  2  2  2
1  1  0  8
2  4  0  9

<小时>

print (np.concatenate([df1.values, df2.values, df3.values]))
[[8 8 3]
 [7 7 0]
 [4 2 5]
 [2 2 2]
 [1 0 8]
 [4 0 9]]

df = pd.DataFrame(np.concatenate([df1.values, df2.values, df3.values]), columns=df1.columns)
print (df)
   A  B  F
0  8  8  3
1  7  7  0
2  4  2  5
3  2  2  2
4  1  0  8
5  4  0  9

<小时>

df = pd.concat([df1,df2,df3], ignore_index=True)
print (df)
   A  B  F
0  8  8  3
1  7  7  0
2  4  2  5
3  2  2  2
4  1  0  8
5  4  0  9

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