保存包含numpy数组的pandas数据帧

Question

我有一个数据帧，其中一列充满了numpy数组。

A     B         C
0   1.0   0.000000  [[0. 1.],[0. 1.]]
1   2.0   0.000000  [[85. 1.],[52. 0.]]
2   3.0   0.000000  [[5. 1.],[0. 0.]]
3   1.0   3.333333  [[0. 1.],[41. 0.]]
4   2.0   3.333333  [[85. 1.],[0. 21.]]

问题是，当我将其保存为CSV文件，并将其加载到另一个python文件时，numpy列将被读取为文本。

我尝试用np.fromstring()或np.loadtxt()转换列，但它不起作用。

pd.read_csv()后的和阵列示例

"[[ 85.  1.]n [   52.            0.        ]]"

感谢

Answer 1

您可以尝试.to_json()

output = pd.DataFrame([
{'a':1,'b':np.arange(4)},
{'a':2,'b':np.arange(5)}
]).to_json()

但当你重新加载时，你只会得到列表

df=pd.read_json()

使用将它们转换为numpy数组

df['b']=[np.array(v) for v in df['b']]

Answer 2

下面的代码应该可以工作。我用了另一个问题来解决它，这里有更多的解释：将带括号的字符串转换为numpy数组

import pandas as pd
import numpy as np
from ast import literal_eval
# Recreating DataFrame
data = np.array([0, 1, 0, 1, 85, 1, 52, 0, 5, 1, 0, 0, 0, 1, 41, 0, 85, 1, 0, 21], dtype='float')
data = data.reshape((5,2,2))
write_df = pd.DataFrame({'A': [1.0,2.0,3.0,1.0,2.0],
'B': [0,0,0,3+1/3,3+1/3],
'C': data.tolist()})
# Saving DataFrame to CSV
fpath = 'D:\Data\test.csv'
write_df.to_csv(fpath)
# Reading DataFrame from CSV
read_df = pd.read_csv(fpath)
# literal_eval converts the string to a list of tuples
# np.array can convert this list of tuples directly into an array
def makeArray(rawdata):
string = literal_eval(rawdata)
return np.array(string)
# Applying the function row-wise, there could be a more efficient way
read_df['C'] = read_df['C'].apply(lambda x: makeArray(x))

Answer 3

这里有一个丑陋的解决方案。

import pandas as pd
import numpy as np
### Create dataframe
a = [1.0, 2.0, 3.0, 1.0, 2.0]
b = [0.000000,0.000000,0.000000,3.333333,3.333333]
c = [np.array([[0. ,1.],[0. ,1.]]),
np.array([[85. ,1.2],[52. ,0.]]),
np.array([[5. ,1.],[0. ,0.]]),
np.array([[0. ,1.],[41. ,0.]]),
np.array([[85. ,1.],[0. ,21.]]),]

df = pd.DataFrame({"a":a,"b":b,"c":c})
#### Save to csv
df.to_csv("to_trash.csv")
df = pd.read_csv("to_trash.csv")
### Bad string manipulation that could be done better with regex
df["c"] = ("np.array("+(df
.c
.str.split()
.str.join(' ')
.str.replace(" ",",")
.str.replace(",,",",")
.str.replace("[,", "[", regex=False)
)+")").apply(lambda x: eval(x))

Answer 4

我找到的最好的解决方案是使用Pickle文件。

您可以将数据帧保存为pickle文件。

import pickle
img = cv2.imread('img1.jpg')
data = pd.DataFrame({'img':img})
data.to_pickle('dataset.pkl')

然后你可以阅读是作为泡菜文件：

with (open(ref_path + 'dataset.pkl', "rb")) as openfile:
df_file = pickle.load(openfile)

如果有效，请告诉我。