The info() Function in PythonIn this tutorial, we will learn about the Python pandas method df.info() Method. Pandas is a very popular library to analyze data in easy and effective. It is an important and widely used method of Python. This Method prints the information or summary of the dataframe. It prints the various information of the Dataframe such as index type, dtype, columns, non-values, and memory usage. It gives a quick overview of the dataset. Let’s see the syntax of using it. Syntax:Parameters –
Now, let’s understand it usage in Pandas Dataframe. Usage of info() MethodWe are using the Iris dataframe to perform some operations. It can be downloaded at www.kaggle.com. Example – 1: Output: Id SepalLengthCm SepalWidthCm PetalLengthCm PetalWidthCm Species 0 1 5.1 3.5 1.4 0.2 Iris-setosa 1 2 4.9 3.0 1.4 0.2 Iris-setosa 2 3 4.7 3.2 1.3 0.2 Iris-setosa 3 4 4.6 3.1 1.5 0.2 Iris-setosa 4 5 5.0 3.6 1.4 0.2 Iris-setosa .. ... ... ... ... ... ... 145 146 6.7 3.0 5.2 2.3 Iris-virginica 146 147 6.3 2.5 5.0 1.9 Iris-virginica 147 148 6.5 3.0 5.2 2.0 Iris-virginica 148 149 6.2 3.4 5.4 2.3 Iris-virginica 149 150 5.9 3.0 5.1 1.8 Iris-virginica Now we will print the summary of the dataframe. Output: The dataframe details is: <class 'pandas.core.frame.DataFrame'> RangeIndex: 150 entries, 0 to 149 Data columns (total 6 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 Id 150 non-null int64 1 SepalLengthCm 150 non-null float64 2 SepalWidthCm 150 non-null float64 3 PetalLengthCm 150 non-null float64 4 PetalWidthCm 150 non-null float64 5 Species 150 non-null object dtypes: float64(4), int64(1), object(1) memory usage: 7.2+ KB Explanation – As we can see that, the info() method printed the complete summary of the given dataframe. The summary includes the list of all columns with their data types and the number of non-values in each column. Example – 2: Print the short summary of DataframeTo print the short summary of the dataframe, we need to pass the verbose parameter as False in the info() method. Let’s understand the following example. Example – Output: The short summary of dataframe is: <class 'pandas.core.frame.DataFrame'> RangeIndex: 150 entries, 0 to 149 Columns: 6 entries, Id to Species dtypes: float64(4), int64(1), object(1) memory usage: 7.2+ KB The above summary is concise. It is helpful when we have 1000s of attributes in dataframe. Example – 3: Exclude the null count valuesWe can omit the null value count parameter by passing False. Let’s understand the following example. Example – Output: The short summary of dataframe is: d:/Python Project/listproblems.py:333: FutureWarning: null_counts is deprecated. Use show_counts instead print(df.info(null_counts=False)) <class 'pandas.core.frame.DataFrame'> RangeIndex: 150 entries, 0 to 149 Data columns (total 6 columns): # Column Dtype --- ------ ----- 0 Id int64 1 SepalLengthCm float64 2 SepalWidthCm float64 3 PetalLengthCm float64 4 PetalWidthCm float64 5 Species object dtypes: float64(4), int64(1), object(1) memory usage: 7.2+ KB ConclusionWe have discussed the importance of the info() method and its index. We have passed the various parameters and printed the various format of the summary. |
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