<jupyter_start><jupyter_text>**Pandas is imported and ready to use**<jupyter_code>import pandas

mydataset = {
  'cars': ["BMW", "Volvo", "Ford"],
  'passings': [3, 7, 2]
}

myvar = pandas.DataFrame(mydataset)

print(myvar)<jupyter_output><empty_output><jupyter_text>**Create an alias with the as keyword while importing**<jupyter_code>import pandas as pd

mydataset = {
  'cars': ["BMW", "Volvo", "Ford"],
  'passings': [3, 7, 2]
}

myvar = pd.DataFrame(mydataset)

print(myvar)<jupyter_output><empty_output><jupyter_text>**Checking Pandas Version**<jupyter_code>import pandas as pd

print(pd.__version__)<jupyter_output><empty_output><jupyter_text>**A Pandas Series is like a column in a table.**<jupyter_code>import pandas as pd

a = [1, 7, 2]

myvar = pd.Series(a)

print(myvar)<jupyter_output><empty_output><jupyter_text>**With the index argument, you can name your own labels**<jupyter_code>import pandas as pd

a = [1, 7, 2]

myvar = pd.Series(a, index = ["x", "y", "z"])

print(myvar)<jupyter_output><empty_output><jupyter_text>**Create a simple Pandas Series from a dictionary**<jupyter_code>import pandas as pd

calories = {"day1": 420, "day2": 380, "day3": 390}

myvar = pd.Series(calories)

print(myvar)<jupyter_output><empty_output><jupyter_text>**Create a Series using only data from "day1" and "day2"**<jupyter_code>import pandas as pd

calories = {"day1": 420, "day2": 380, "day3": 390}

myvar = pd.Series(calories, index = ["day1", "day2"])

print(myvar)<jupyter_output><empty_output><jupyter_text>**Create a DataFrame from two Series**<jupyter_code>import pandas as pd

data = {
  "calories": [420, 380, 390],
  "duration": [50, 40, 45]
}

myvar = pd.DataFrame(data)

print(myvar)<jupyter_output><empty_output><jupyter_text>**Create a simple Pandas DataFrame**<jupyter_code>import pandas as pd

data = {
  "calories": [420, 380, 390],
  "duration": [50, 40, 45]
}

#load data into a DataFrame object:
df = pd.DataFrame(data)

print(df)<jupyter_output><empty_output><jupyter_text>**With the index argument, you can name your own indexes**<jupyter_code>import pandas as pd

data = {
  "calories": [420, 380, 390],
  "duration": [50, 40, 45]
}

df = pd.DataFrame(data, index = ["day1", "day2", "day3"])

print(df)<jupyter_output><empty_output>
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{'chain_length': '10', 'dir': 'jupyter-structured-clean-dedup', 'id': '647554', 'license': 'Apache-2.0', 'n_tokens_mistral': 972, 'n_tokens_neox': 882, 'n_words': 209, 'path': 'Pandas_1.ipynb', 'repo_name': 'Samuel-Jayasingh/Tutorials', 'size': '2258'}