A quick introduction to Pandas for beginners

Learning Pandas in 60 minutes!

Pandas is a popular open-source data manipulation library for the Python programming language, widely used for data analysis and data science tasks.

import numpy as np
import pandas as pd

Object creation

You can create a Series in pandas by providing a list of values, which will result in pandas assigning a default integer index.

s = pd.Series([1, 3, 5, np.nan, 6, 8])

s 
0    1.0
1    3.0
2    5.0
3    NaN
4    6.0
5    8.0
dtype: float64

To create a DataFrame in pandas, you can pass a NumPy array and specify a datetime index using the date_range() function. You can also label the columns of the DataFrame.

dates = pd.date_range("20130101", periods=6)

dates
DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04',
               '2013-01-05', '2013-01-06'],
              dtype='datetime64[ns]', freq='D')
df = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list("ABCD"))
df 
                   A         B         C         D
2013-01-01  0.469112 -0.282863 -1.509059 -1.135632
2013-01-02  1.212112 -0.173215  0.119209 -1.044236
2013-01-03 -0.861849 -2.104569 -0.494929  1.071804
2013-01-04  0.721555 -0.706771 -1.039575  0.271860
2013-01-05 -0.424972  0.567020  0.276232 -1.087401
2013-01-06 -0.673690  0.113648 -1.478427  0.524988

In pandas, you can create a DataFrame by providing a dictionary of objects that can be converted into a series-like structure.

df2 = pd.DataFrame(
{
         "A": 1.0,
         "B": pd.Timestamp("20130102"),
         "C": pd.Series(1, index=list(range(4)), dtype="float32"),
         "D": np.array([3] * 4, dtype="int32"),
         "E": pd.Categorical(["test", "train", "test", "train"]),
         "F": "foo",
     }
 ) 

In [10]: df2
Out[10]: 
     A          B    C  D      E    F
0  1.0 2013-01-02  1.0  3   test  foo
1  1.0 2013-01-02  1.0  3  train  foo
2  1.0 2013-01-02  1.0  3   test  foo
3  1.0 2013-01-02  1.0  3  train  foo

The resulting DataFrame contains columns with varying data types.