Write Dictionary of Lists to a CSV File

Write dictionary of lists to a CSV file

If you don't care about the order of your columns (since dictionaries are unordered), you can simply use zip():

d = {"key1": [1,2,3], "key2": [4,5,6], "key3": [7,8,9]}
with open("test.csv", "wb") as outfile:
   writer = csv.writer(outfile)
   writer.writerow(d.keys())
   writer.writerows(zip(*d.values()))

Result:

key3    key2    key1
7       4       1
8       5       2
9       6       3

If you do care about order, you need to sort the keys:

keys = sorted(d.keys())
with open("test.csv", "wb") as outfile:
   writer = csv.writer(outfile, delimiter = "\t")
   writer.writerow(keys)
   writer.writerows(zip(*[d[key] for key in keys]))

Result:

key1    key2    key3
1       4       7
2       5       8
3       6       9

Write dictionary of lists to csv

I wanted to do the same thing and this is what worked for me. Using the zip with the * operator did the trick for me. Also paying attention to the writerow singular and writerows plural helped write the dictionary into the kind of file I wanted with headers.

    zd = zip(*dictionary.values())
    with open('file.csv', 'w') as file:
        writer = csv.writer(file, delimiter=',')
        writer.writerow(dictionary.keys())
        writer.writerows(zd)

Output looks like this,

gender,age,state,race,weights,educ
1,39,32,06,0.57,8
2,35,33,06,0.93,5
1,39,11,06,0.83,5

Your example should work exactly the same only change dictionary to be the dictionary with your data in it.

Saving a python dictionary (of lists) in a csv file

If you can use pandas its very simple.

Demo:

import pandas as pd
d = {"key1": [1,2,3], "key2": [5], "key3": [6,9]}
df = pd.DataFrame.from_dict(d, orient='index')
df = df.transpose()
df.to_csv("test.csv", index=False)

Write dictionary of different size lists to a CSV via Python

You can use this code:

import pandas as pd 
dictionary = {'Odd': [1,3,5,7,9], 'Even': [2,4,6], 'Operations': ['-','+','*','\\']}

# These lines are because your lists are not all of the same length 
df = pd.DataFrame.from_dict(dictionary, orient='index')
df = df.transpose()

# Pandas was converting the "9" in odd to a float, this undoes that 
df["Odd"] = pd.to_numeric(df["Odd"], downcast="integer")

# index = False says don't include the index that pandas slaps onto your data  
# This writes to output.csv as you'd expect 
df.to_csv("output.csv", index = False)

How to write a dictionary of lists with different length to csv?

import pandas as pd
dic = {'a': ['ACI', 'BBY', 'AMRX'], 'b': ['ABM', 'AG']} 
df = pd.DataFrame.from_dict(dic, orient='index') #Convert dict to df
print(df)
df.to_csv("final.csv",header=False) #Convert df to csv

Write list of dictionaries with additional lists to CSV - Python

This type of list of the dictionary is called Nested JSON; it is better to handle this data type to CSV with Pandas method json_normalize :

import pandas as pd

test = [{
    'name': 'name_1', 
    'id': 'id_1', 
    'info': [{
        'info_1': 'some info',
        'info_2': 'more info'
        },
        {
        'info_1': 'all the info',
        'info_2': 'extra info'
    }]
 },
 {    
    'name': 'name_2', 
    'id': 'id_2', 
    'info': [{
        'info_1': 'another piece of info the same type as info_1 above',
        'info_2': 'info'
        },
        {
        'info_1': 'getting tedious',
        'info_2': 'you get the picture...'
        }
    ]
}]

df = pd.json_normalize(test, 'info', ['id', 'name'], 
                    record_prefix='information_')

df.to_csv('information.csv')

final result(screenshot):

*: it is better to use Pandas for this problem instead of CSV standard library because if you have a large file, 2 iteration to handle this problem has much time processing.

Convert dictionary of lists to a CSV file using Python

Why are you trying to use a dictionary? You can use the csv module and write those lists directly.

import csv

header_column = ["id", "data"]
text = ["1, first", "2, second", "3, third"]

with open('sample.tsv', 'wb') as f:
    writer = csv.writer(f, delimiter='\t')
    writer.writerow(header_column)
    for l in text:
        writer.writerow(l.split(', '))

This works as expected, giving

id  data
1   first
2   second
3   third

Do note for excel to understand that your code is tab separated, you need to save it as a .tsv file.

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