Python script to write list of dict with multiple values to multiple files
I have a list of dicts as shown below. I wish to write the dicts to multiple excel or csv files depending on the keys. if the keys are the same they should be in one file.
my_list_of_dicts:
[{'john': ['0', '100']}, {'john': ['4', '101']}, {'john': ['0', '102']}, {'mary': ['2', '100']}, {'mary': ['5', '101']}, {'mary': ['4', '102']}, {'mary': ['1', '103']}, {'sam': ['4', '100']}, {'sam': ['3', '101']}, {'sam': ['12', '102']}, {'paul': ['2', '100']}, {'hay': ['2', '100']}, {'hay': ['1', '102']}, {'mercy': ['4', '101']}]
My code so far:
x =
i = 0
for ii, line in enumerate(my_list_of_dicts):
with open("out_%s.csv" % i, 'w+') as f:
if line.keys() not in x:
x.append(line.keys())
i += 1
pd.DataFrame.from_dict(data=line, orient='index').to_csv(f, header=False)
else:
pd.DataFrame.from_dict(data=line, orient='index').to_csv(f, header=False)
Result:
I am getting the desired number of files but not the content.
Expectation:
I expect to get files corresponding to each key i.e (john, mary, sam, jay, paul, hay, and mercy) with the below content. Using john as example:
john, 0, 100
john, 4, 101
john, 0, 102
I am not sure how to proceed or if I even need enumerate. Thank you
python pandas csv pandas-groupby
edited Nov 27 '18 at 0:04
jpp
101k2163112
asked Nov 26 '18 at 23:44
StarterStarter
717
add a comment |
I have a list of dicts as shown below. I wish to write the dicts to multiple excel or csv files depending on the keys. if the keys are the same they should be in one file.
my_list_of_dicts:
[{'john': ['0', '100']}, {'john': ['4', '101']}, {'john': ['0', '102']}, {'mary': ['2', '100']}, {'mary': ['5', '101']}, {'mary': ['4', '102']}, {'mary': ['1', '103']}, {'sam': ['4', '100']}, {'sam': ['3', '101']}, {'sam': ['12', '102']}, {'paul': ['2', '100']}, {'hay': ['2', '100']}, {'hay': ['1', '102']}, {'mercy': ['4', '101']}]
My code so far:
x =
i = 0
for ii, line in enumerate(my_list_of_dicts):
with open("out_%s.csv" % i, 'w+') as f:
if line.keys() not in x:
x.append(line.keys())
i += 1
pd.DataFrame.from_dict(data=line, orient='index').to_csv(f, header=False)
else:
pd.DataFrame.from_dict(data=line, orient='index').to_csv(f, header=False)
Result:
I am getting the desired number of files but not the content.
Expectation:
I expect to get files corresponding to each key i.e (john, mary, sam, jay, paul, hay, and mercy) with the below content. Using john as example:
john, 0, 100
john, 4, 101
john, 0, 102
I am not sure how to proceed or if I even need enumerate. Thank you
python pandas csv pandas-groupby
edited Nov 27 '18 at 0:04
jpp
101k2163112
asked Nov 26 '18 at 23:44
StarterStarter
717
Do you mean to use i instead of ii in your for loop?
– Jack Moody
Nov 26 '18 at 23:52
No that is why I said I was not sure if using enumerate was the right idea cos the ii was not used
– Starter
Nov 26 '18 at 23:55
Normally if you aren’t going to use something like that you would use _
– Jack Moody
Nov 26 '18 at 23:57
1
Okay now I know. Thank you
– Starter
Nov 27 '18 at 0:04
add a comment |
I have a list of dicts as shown below. I wish to write the dicts to multiple excel or csv files depending on the keys. if the keys are the same they should be in one file.
my_list_of_dicts:
[{'john': ['0', '100']}, {'john': ['4', '101']}, {'john': ['0', '102']}, {'mary': ['2', '100']}, {'mary': ['5', '101']}, {'mary': ['4', '102']}, {'mary': ['1', '103']}, {'sam': ['4', '100']}, {'sam': ['3', '101']}, {'sam': ['12', '102']}, {'paul': ['2', '100']}, {'hay': ['2', '100']}, {'hay': ['1', '102']}, {'mercy': ['4', '101']}]
My code so far:
x =
i = 0
for ii, line in enumerate(my_list_of_dicts):
with open("out_%s.csv" % i, 'w+') as f:
if line.keys() not in x:
x.append(line.keys())
i += 1
pd.DataFrame.from_dict(data=line, orient='index').to_csv(f, header=False)
else:
pd.DataFrame.from_dict(data=line, orient='index').to_csv(f, header=False)
Result:
I am getting the desired number of files but not the content.
Expectation:
I expect to get files corresponding to each key i.e (john, mary, sam, jay, paul, hay, and mercy) with the below content. Using john as example:
john, 0, 100
john, 4, 101
john, 0, 102
I am not sure how to proceed or if I even need enumerate. Thank you
python pandas csv pandas-groupby
edited Nov 27 '18 at 0:04
jpp
101k2163112
asked Nov 26 '18 at 23:44
StarterStarter
717
I have a list of dicts as shown below. I wish to write the dicts to multiple excel or csv files depending on the keys. if the keys are the same they should be in one file.
my_list_of_dicts:
[{'john': ['0', '100']}, {'john': ['4', '101']}, {'john': ['0', '102']}, {'mary': ['2', '100']}, {'mary': ['5', '101']}, {'mary': ['4', '102']}, {'mary': ['1', '103']}, {'sam': ['4', '100']}, {'sam': ['3', '101']}, {'sam': ['12', '102']}, {'paul': ['2', '100']}, {'hay': ['2', '100']}, {'hay': ['1', '102']}, {'mercy': ['4', '101']}]
My code so far:
x =
i = 0
for ii, line in enumerate(my_list_of_dicts):
with open("out_%s.csv" % i, 'w+') as f:
if line.keys() not in x:
x.append(line.keys())
i += 1
pd.DataFrame.from_dict(data=line, orient='index').to_csv(f, header=False)
else:
pd.DataFrame.from_dict(data=line, orient='index').to_csv(f, header=False)
Result:
I am getting the desired number of files but not the content.
Expectation:
I expect to get files corresponding to each key i.e (john, mary, sam, jay, paul, hay, and mercy) with the below content. Using john as example:
john, 0, 100
john, 4, 101
john, 0, 102
I am not sure how to proceed or if I even need enumerate. Thank you
python pandas csv pandas-groupby
python pandas csv pandas-groupby
edited Nov 27 '18 at 0:04
jpp
101k2163112
asked Nov 26 '18 at 23:44
StarterStarter
717
edited Nov 27 '18 at 0:04
jpp
101k2163112
asked Nov 26 '18 at 23:44
StarterStarter
717
edited Nov 27 '18 at 0:04
jpp
101k2163112
edited Nov 27 '18 at 0:04
jpp
101k2163112
edited Nov 27 '18 at 0:04
jpp
101k2163112
101k2163112
asked Nov 26 '18 at 23:44
StarterStarter
717
asked Nov 26 '18 at 23:44
StarterStarter
717
asked Nov 26 '18 at 23:44
StarterStarter
717
717
Do you mean to use i instead of ii in your for loop?
– Jack Moody
Nov 26 '18 at 23:52
No that is why I said I was not sure if using enumerate was the right idea cos the ii was not used
– Starter
Nov 26 '18 at 23:55
Normally if you aren’t going to use something like that you would use _
– Jack Moody
Nov 26 '18 at 23:57
1
Okay now I know. Thank you
– Starter
Nov 27 '18 at 0:04
add a comment |
Do you mean to use i instead of ii in your for loop?
– Jack Moody
Nov 26 '18 at 23:52
No that is why I said I was not sure if using enumerate was the right idea cos the ii was not used
– Starter
Nov 26 '18 at 23:55
Normally if you aren’t going to use something like that you would use _
– Jack Moody
Nov 26 '18 at 23:57
1
Okay now I know. Thank you
– Starter
Nov 27 '18 at 0:04
Do you mean to use i instead of ii in your for loop?
– Jack Moody
Nov 26 '18 at 23:52
Do you mean to use i instead of ii in your for loop?
– Jack Moody
Nov 26 '18 at 23:52
No that is why I said I was not sure if using enumerate was the right idea cos the ii was not used
– Starter
Nov 26 '18 at 23:55
No that is why I said I was not sure if using enumerate was the right idea cos the ii was not used
– Starter
Nov 26 '18 at 23:55
Normally if you aren’t going to use something like that you would use _
– Jack Moody
Nov 26 '18 at 23:57
Normally if you aren’t going to use something like that you would use _
– Jack Moody
Nov 26 '18 at 23:57
1
1
Okay now I know. Thank you
– Starter
Nov 27 '18 at 0:04
Okay now I know. Thank you
– Starter
Nov 27 '18 at 0:04
add a comment |
1 Answer
1
active
oldest
votes
A better idea is to aggregate your data into a single dataframe and then iterate a groupby object:
# construct dataframe from list of dictionaries
df = pd.DataFrame([[k, *v] for dct in L for k, v in dct.items()])
df[[1, 2]] = df[[1, 2]].apply(pd.to_numeric)
# iterate groupby object and export to separate CSV files
for key, df_key in df.groupby(0):
df_key.to_csv(f'{key}.csv', index=False, header=False)
answered Nov 26 '18 at 23:51
jppjpp
101k2163112
add a comment |
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1 Answer
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active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
A better idea is to aggregate your data into a single dataframe and then iterate a groupby object:
# construct dataframe from list of dictionaries
df = pd.DataFrame([[k, *v] for dct in L for k, v in dct.items()])
df[[1, 2]] = df[[1, 2]].apply(pd.to_numeric)
# iterate groupby object and export to separate CSV files
for key, df_key in df.groupby(0):
df_key.to_csv(f'{key}.csv', index=False, header=False)
answered Nov 26 '18 at 23:51
jppjpp
101k2163112
add a comment |
A better idea is to aggregate your data into a single dataframe and then iterate a groupby object:
# construct dataframe from list of dictionaries
df = pd.DataFrame([[k, *v] for dct in L for k, v in dct.items()])
df[[1, 2]] = df[[1, 2]].apply(pd.to_numeric)
# iterate groupby object and export to separate CSV files
for key, df_key in df.groupby(0):
df_key.to_csv(f'{key}.csv', index=False, header=False)
answered Nov 26 '18 at 23:51
jppjpp
101k2163112
add a comment |
A better idea is to aggregate your data into a single dataframe and then iterate a groupby object:
# construct dataframe from list of dictionaries
df = pd.DataFrame([[k, *v] for dct in L for k, v in dct.items()])
df[[1, 2]] = df[[1, 2]].apply(pd.to_numeric)
# iterate groupby object and export to separate CSV files
for key, df_key in df.groupby(0):
df_key.to_csv(f'{key}.csv', index=False, header=False)
answered Nov 26 '18 at 23:51
jppjpp
101k2163112
A better idea is to aggregate your data into a single dataframe and then iterate a groupby object:
# construct dataframe from list of dictionaries
df = pd.DataFrame([[k, *v] for dct in L for k, v in dct.items()])
df[[1, 2]] = df[[1, 2]].apply(pd.to_numeric)
# iterate groupby object and export to separate CSV files
for key, df_key in df.groupby(0):
df_key.to_csv(f'{key}.csv', index=False, header=False)
answered Nov 26 '18 at 23:51
jppjpp
101k2163112
answered Nov 26 '18 at 23:51
jppjpp
101k2163112
answered Nov 26 '18 at 23:51
jppjpp
101k2163112
answered Nov 26 '18 at 23:51
jppjpp
101k2163112
101k2163112
add a comment |
add a comment |
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Do you mean to use i instead of ii in your for loop?
– Jack Moody
Nov 26 '18 at 23:52
No that is why I said I was not sure if using enumerate was the right idea cos the ii was not used
– Starter
Nov 26 '18 at 23:55
Normally if you aren’t going to use something like that you would use _
– Jack Moody
Nov 26 '18 at 23:57
1
Okay now I know. Thank you
– Starter
Nov 27 '18 at 0:04