Reputation: 143
I have 5 DataFrame
with columns 'day', 'number', 'id', 'recordDay', and I put all the 5 dataframes in a dictionary
. I would like to save 5 dataframes in 5 CSV files with file names based on 'id' and 'recordDay'. Here's the example of dataframe1 and dataframe2
df1 df2
day number id recordDay day number id recordDay
2017-03-21 17 1 1990-01-01 2016-03-21 6 2 1991-02-01
2017-03-22 19 1 1990-01-01 2016-03-22 8 2 1991-02-01
2017-03-23 21 1 1990-01-01 2016-03-23 10 2 1991-02-01
Is it possible to save 5 CSV files with file names like this, 'id_1_1991_01_01.csv'
, 'id_2_1991_02_01.csv'
, 'id_3_1991_03_01.csv'
,'id_4_1991_04_01.csv'
, 'id_5_1991_05_01.csv'
Or 'id_1.csv'
...'id_5.csv'
would be better?
I used the following code, but it only saved one CSV file.
pd.concat(df_dict).to_csv('data.csv', index = False, data_format = '%Y-%m-%d)
Upvotes: 2
Views: 10139
Reputation: 1497
Iterate over the dictionary - using .iloc[] to get the recordID and id values for the name.
df1 = pandas.DataFrame(numpy.random.randn(3, 4), columns=[["day", "number", "id", "recordDay"]])
df2 = pandas.DataFrame(numpy.random.randn(3, 4), columns=[["day", "number", "id", "recordDay"]])
df3 = pandas.DataFrame(numpy.random.randn(3, 4), columns=[["day", "number", "id", "recordDay"]])
df_dict={"data_frame1":df1, "data_frame2": df2, "data_frame3": df3}
for name, df in df_dict.items():
#get the id and recordDay values from each df
df_id=df['id'].iloc[0]
df_record_day=df['recordDay'].iloc[0]
#generate a unique file name based on the id and record
file_name="id_"+str(df_id)+"_"+str(df_record_day)+".csv"
#create the CSV
df.to_csv(file_name, index = False, data_format = '%Y-%m-%d')
Or you can use a list of arrays instead of a dictionary
df_list=[df1, df2, df3]
for df in df_list:
#get the id and recordDay values from each df
df_id=df['id'].iloc[0]
df_record_day=df['recordDay'].iloc[0]
#generate a unique file name based on the id and record
file_name="id_"+str(df_id)+"_"+str(df_record_day)+".csv"
#create the CSV
df.to_csv(file_name, index = False, data_format = '%Y-%m-%d')
Upvotes: 4