Use zip on the three lists (I've corrected the date_list's format, the Original post doesn't have it in correct strings):
>>> date_list = ["Mar 27 2015", "Mar 26 2015", "Mar 25 2015"] >>>
num_list_1 = [22, 35, 7] >>>
num_list_2 = [15, 12, 2] >>>
list(zip(date_list, num_list_1, num_list_2))[('Mar 27 2015', 22, 15), ('Mar 26 2015', 35, 12), ('Mar 25 2015', 7, 2)]And as a single list using a simple list comprehension in conjunction with zip:
>>> [item
for items in zip(date_list, num_list_1, num_list_2) for item in items
]
['Mar 27 2015', 22, 15, 'Mar 26 2015', 35, 12, 'Mar 25 2015', 7, 2]If you wanted this in a dataframe then you can just construct a dict with your lists as the column values:
In [10]:
date_list = ['Mar 27 2015', 'Mar 26 2015', 'Mar 25 2015']
num_list_1 = [22, 35, 7]
num_list_2 = [15, 12, 2]
df = pd.DataFrame({'Date':date_list, 'num1':num_list_1, 'num2':num_list_2})
In [11]:
df['Date'] = pd.to_datetime(df['Date'])
df
Out[11]:
Date num1 num2
0 2015-03-27 22 15
1 2015-03-26 35 12
2 2015-03-25 7 2
In [12]:
df.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 3 entries, 0 to 2
Data columns (total 3 columns):
Date 3 non-null datetime64[ns]
num1 3 non-null int64
num2 3 non-null int64
dtypes: datetime64[ns](1), int64(2)
memory usage: 96.0 bytes
Note: This answer is not pandas anycodings_python dependent, if you are looking for a way anycodings_python to do this in pandas, check @EdChum's anycodings_python answer.,And as a single list using a simple list anycodings_python comprehension in conjunction with zip:,How do I combine the lists so my end result anycodings_python is something like this:,I have my separate lists and I have the anycodings_python database insert working. What I'm not sure anycodings_python about is the proper way to combine the anycodings_python lists. Am I looking for a pandas dataframe? anycodings_python Or something else?
Suppose I have the following example:
date_list = [Mar 27 2015, Mar 26 2015, Mar 25 2015] num_list_1 = [22, 35, 7] num_list_2 = [15, 12, 2]
How do I combine the lists so my end result anycodings_python is something like this:
combined_list = [Mar 27 2015, 22, 15 Mar 26 2015, 35, 12 Mar 25 2015, 7, 2 ]
Use zip on the three lists (I've anycodings_python corrected the date_list's format, the anycodings_python Original post doesn't have it in correct anycodings_python strings):
>>> date_list = ["Mar 27 2015", "Mar 26 2015", "Mar 25 2015"] >>>
num_list_1 = [22, 35, 7] >>>
num_list_2 = [15, 12, 2] >>>
list(zip(date_list, num_list_1, num_list_2))[('Mar 27 2015', 22, 15), ('Mar 26 2015', 35, 12), ('Mar 25 2015', 7, 2)]And as a single list using a simple list anycodings_python comprehension in conjunction with zip:
>>> [item
for items in zip(date_list, num_list_1, num_list_2) for item in items
]
['Mar 27 2015', 22, 15, 'Mar 26 2015', 35, 12, 'Mar 25 2015', 7, 2]If you wanted this in a dataframe then anycodings_python you can just construct a dict with your anycodings_python lists as the column values:
In [10]:
date_list = ['Mar 27 2015', 'Mar 26 2015', 'Mar 25 2015']
num_list_1 = [22, 35, 7]
num_list_2 = [15, 12, 2]
df = pd.DataFrame({'Date':date_list, 'num1':num_list_1, 'num2':num_list_2})
In [11]:
df['Date'] = pd.to_datetime(df['Date'])
df
Out[11]:
Date num1 num2
0 2015-03-27 22 15
1 2015-03-26 35 12
2 2015-03-25 7 2
In [12]:
df.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 3 entries, 0 to 2
Data columns (total 3 columns):
Date 3 non-null datetime64[ns]
num1 3 non-null int64
num2 3 non-null int64
dtypes: datetime64[ns](1), int64(2)
memory usage: 96.0 bytes
Here, the three lists are combined together using + operator. This is used because the + operator is one of the easiest ways to combine multiple lists into a single one. ,Here the (*) operator is used for merging the three lists together while maintaining the order of the elements. The (*) operator is utilized here as multiple lists can be easily added using it. ,Concatenation is one of the easiest ways to combine list elements or strings while codding in Python. But while using the chains() method, import the itertools module using the import statement. Additionally, you can also use methods such as join() to concatenate two strings.,We can observe that the shorthand version of a for loop is used here for concatenation. This list comprehension technique is used to avoid writing multiple inner loops, as there are three lists that have to be added. As a result, the process is fast and efficient.
Example:
# Python program to merge lists
# Using + Operator
# Initializing lists
list1 = [2, 3, 4, 2, 2]
list2 = [4, 5, 6, 7, 34, 56]
list3 = [1, 5, 33, 2, 34, 46]
# merge lists using + Operator
newlist = list1 + list2 + list3
# Print output
print('Merged List: ', newlist)Output:
Merged List: [2, 3, 4, 2, 2, 4, 5, 6, 7, 34, 56, 1, 5, 33, 2, 34, 46]
Example:
# Python program to concatenate lists
# Using extend
function
# Initializing lists
list1 = [2, 3, 4, 2, 2]
list2 = [4, 5, 6, 7, 34, 56]
list3 = [4, 67, 2, 2, 4, 66]
# concatenate lists using extend()
list1.extend(list2)
list1.extend(list3)
# Print output
print('Concatenated List: ', list1)Output
Concatenated List: [2, 3, 4, 2, 2, 4, 5, 6, 7, 34, 56, 1, 5, 33, 2, 34, 46]
Single Line Code Example:
# Python program to concatenate lists # Initializing lists list1 = [2, 3, 4, 2, 2] list2 = [4, 5, 6, 7, 34, 56] list3 = [1, 5, 33, 2, 34, 46] # Concatenate lists newlist = [y for x in [list1, list2, list3] for y in x ] # Print output print(Concatenated List: ',newlist)
Last Updated : 03 Dec, 2020
Concatenated list using naive method: [1, 4, 5, 6, 5, 3, 5, 7, 2, 5]
Concatenated list using +: [1, 4, 5, 6, 5, 3, 5, 7, 2, 5]
Concatenated list using list comprehension: [1, 4, 5, 6, 5, 3, 5, 7, 2, 5]
Concatenated list using list.extend(): [1, 4, 5, 6, 5, 3, 5, 7, 2, 5]
Concatenated list using * operator: [1, 4, 5, 6, 5, 3, 5, 7, 2, 5]
If we want to combine two lists in R, we can simply use the c() function:,Now, let’s combine these two lists into only one list…,Example: Append Two Lists in R with c() Function,Example: Append Two Lists in R with append() Function
list1 < -list(A = "A1", B = "B1", C = "C1") # Create first example list list1 # Print first example list # $A #[1] "A1" # # $B #[1] "B1" # # $C #[1] "C1"
list2 < -list(X = 1: 3, Y = 10: 5) # Create second example list list2 # Print second example list # $X #[1] 1 2 3 # # $Y #[1] 10 9 8 7 6 5
list12 < -c(list1, list2) # Merge two lists list12 # Print merged list # $A #[1] "A1" # # $B #[1] "B1" # # $C #[1] "C1" # # $X #[1] 1 2 3 # # $Y #[1] 10 9 8 7 6 5
append(list1, list2) # Apply append function in R
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list_one = [7, 6, 5] list_two = [4, 3, 2]
#horizontallymerged_list = list_one + list_twomerged_list
[7, 6, 5, 4, 3, 2]#vertically
import numpy as np
np.vstack((list_one, list_two))array([ [7, 6, 5], [4, 3, 2] ])