<jupyter_start><jupyter_text>---title: "Pandas-Concatenation"author: "<NAME>"date: 2020-09-04description: "-"type: technical_notedraft: false---<jupyter_code>import numpy as np
import scipy.stats
import pandas as pd
import sklearn
one = pd.DataFrame({
   'Name': ['Alex', 'Amy', 'Allen', 'Alice', 'Ayoung'],
   'subject_id':['sub1','sub2','sub4','sub6','sub5'],
   'Marks_scored':[98,90,87,69,78]},
   index=[1,2,3,4,5])

two = pd.DataFrame({
   'Name': ['Billy', 'Brian', 'Bran', 'Bryce', 'Betty'],
   'subject_id':['sub2','sub4','sub3','sub6','sub5'],
   'Marks_scored':[89,80,79,97,88]},
   index=[1,2,3,4,5])
pd.concat([one,two])
pd.concat([one,two],keys=['x','y'])
pd.concat([one,two],keys=['x','y'],ignore_index=True)
pd.concat([one,two],axis=1)
#Concatenating Using append
one.append(two)
one.append([two,one,two])
#Time Series
pd.datetime.now()
pd.Timestamp('2017-03-01')
pd.Timestamp(1587687255,unit='s')
pd.date_range("11:00", "13:30", freq="30min").time<jupyter_output><empty_output>
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '422841', 'license': 'MIT', 'n_tokens_mistral': 457, 'n_tokens_neox': 422, 'n_words': 57, 'path': 'content/python/pandas/.ipynb_checkpoints/Pandas-Concatenation-checkpoint.ipynb', 'repo_name': 'Palaniappan12345/mlnotes', 'size': '1001'}