in python , How I can save the result to csv , AttributeError: 'dict' object has no attribute 'to_csv'

Question

How I can save the result to csv in arranged way? meaning adding extra columns explain what 'added' and what 'removed' and what 'changed'

I tried diff.to_csv('diff.csv') and got this error

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'dict' object has no attribute 'to_csv'

This is the python code

from csv_diff import load_csv, compare
diff = compare(
    load_csv(open("list1.csv"), key="ean"),
    load_csv(open("list2.csv"), key="ean")
)
diff.to_csv('diff.csv')

Extra information

list1.csv

price, oldprice,title,brand,category,unit,ean,,
17,,VR BOX Virtual Reality 3D Glasses Bluetooth Game Remote Control For Phone Iphone,other,3d glasses,2023700513,272434,,
18,,3d Glasses,other,3d glasses,1493500513,2272434,,
22,,Zefas Active 3D GlassesFor SmartPhones,zefas,3d glasses,1342700513,2272456,,
22.98,,3D Glasses Circular Polarized Lenses for Polarized TV| 3D Cinemas,other,3d glasses,1992100513,2272483,,
25,,max3 pro,other,3d glasses,1904600513,2272432,,
28.27,,Red Blue Clip on Anaglyph Glasses,other,3d glasses,2068900513,2272453,,

list2.csv

price,oldprice,title,brand,category,unit,ean,,
22.98,,3D Glasses Circular Polarized Lenses for Polarized TV| 3D Cinemas,other,3d  glasses,1992100513,2272483,,
25,,max3 pro,other,3d glasses,1904600513,2272432,,
59,,Red-blue Cyan Anaglyph 3D,terratec,3d glasses,2103700513,2272428,,
65,,Sinogoodies Passive 3D GlassesFor SmartPhones,sinogoodies,3d glasses,1603700513,2272464,,
69.91,,G15-DLP 3D Active Shutter Glasses for DLP-LINK DLP LINK 3D for Optoma Sharp LG Acer BenQ Projectors,other,3d glasses,2039200513,227243,,
70,,Sinogoodies Passive 3D GlassesFor Multi,sinogoodies,3d glasses,1603600513,2272464,,

screen Result of running

compare(
        load_csv(open("list1.csv"), key="ean"),
        load_csv(open("list2.csv"), key="ean")
    )

is

{'added': [{'price': '59', 'oldprice': '', 'title': 'Red-blue Cyan Anaglyph 3D',
 'brand': 'terratec', 'category': '3d glasses', 'unit': '2103700513', 'ean': '22
72428', '': ''}, {'price': '70', 'oldprice': '', 'title': 'Sinogoodies Passive 3
D GlassesFor Multi', 'brand': 'sinogoodies', 'category': '3d glasses', 'unit': '
1603600513', 'ean': '2272464', '': ''}, {'price': '69.91', 'oldprice': '', 'titl
e': 'G15-DLP 3D Active Shutter Glasses for DLP-LINK DLP LINK 3D for Optoma Sharp
 LG Acer BenQ Projectors', 'brand': 'other', 'category': '3d glasses', 'unit': '
2039200513', 'ean': '227243', '': ''}], 'removed': [{'price': '17', 'oldprice':
'', 'title': 'VR BOX Virtual Reality 3D Glasses Bluetooth Game Remote Control Fo
r Phone Iphone', 'brand': 'other', 'category': '3d glasses', 'unit': '2023700513
', 'ean': '272434', '': ''}, {'price': '18', 'oldprice': '', 'title': '3d Glasse
s', 'brand': 'other', 'category': '3d glasses', 'unit': '1493500513', 'ean': '22
72434', '': ''}, {'price': '22', 'oldprice': '', 'title': 'Zefas Active 3D Glass
esFor SmartPhones', 'brand': 'zefas', 'category': '3d glasses', 'unit': '1342700
513', 'ean': '2272456', '': ''}, {'price': '28.27', 'oldprice': '', 'title': 'Re
d Blue Clip on Anaglyph Glasses', 'brand': 'other', 'category': '3d glasses', 'u
nit': '2068900513', 'ean': '2272453', '': ''}], 'changed': [], 'columns_added':
[], 'columns_removed': []}

this solution not working

import pandas as pd
dataframe = pd.DataFrame(diff)
dataframe.to_csv("data.csv", header=True)

Answer 1

The other solutions are not working because your data does not have the correct structure for a DataFrame . You need to access the lists of dicts from the top level keys first.

import pandas

df1  = pandas.DataFrame(diff['added'])
df1['change'] = 'added'
df2 = pandas.DataFrame(diff['removed'])
df2['change'] = 'removed'

df = df1.append(df2)
df.to_csv('diff.csv')

Change per Comment Request

df1 = pandas.read_csv('list1.csv')
df1['version'] = 'list1'
df2 = pandas.read_csv('list2.csv')
df2['version'] = 'list2'

# keep only columns 'version', 'ean', 'price'
diff = df1.append(df2)[['version', 'ean', 'price']]
# keep only duplicated eans, which will only occur
# for eans in both original lists
diff = diff[diff['ean'].duplicated(keep=False)]
# perform a pivot https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html
diff = diff.pivot(index='ean', columns='version', values='price')

# back to a normal dataframe
diff = diff.reset_index()
diff.columns.name = None

# rename columns and keep only what we want
diff = diff.rename(columns={'list1': 'price1', 'list2': 'price2'})[['ean', 'price1', 'price2']]
diff['difference'] = diff['price2'] - diff['price1']

Answer 2

you can use to_csv method that's being provided by pandas :

import pandas as pd 

df = pd.DataFrame(dict([ (k,pd.Series(v)) for k,v in diff.items() ]))
df.to_csv('diff.csv')

Answer 3

you can use pandas package pip install pandas

import pandas as pd
added_frame = pd.DataFrame(yourdict['added'])
removed_frame = pd.DataFrame(yourdict['removed'])
df = added_frame.append(removed_frame)
df.to_csv("data.csv", header=True)

Pandas Docs

Answer 4

The error 'dict' object has no attribute 'to_csv' means that your diff variable is a dictionary and therefore has not method called .to_csv .

You could try to coerce your diff into a csv file but it will not work properly. Your diff is currently an dictionary with values that are arrays of dictionaries . This format will not work for csv. If you use the Pandas package you need your dictionary to have values that are arrays of strings . Here is the docs with an example.

I recommend you think about how to format your diff first and then convert to csv.

One option to make this work is to create two csvs from the diff dictionary. The added and removed values are actually in the right format for csv. Here is an example:

import csv

keys = diff['added'][0].keys()
with open('file_name.csv', 'w') as output_file:
  dict_writer = csv.DictWriter(output_file, keys)
  dict_writer.writeheader()
  dict_writer.writerows(diff['added'])

These are the docs for the csv package.

EDIT: keys should get the keys from the first element in added.