Create a simple Pandas Series from a list: import pandas as pd a = [1, 7, 2] myvar = pd.Series(a) ... myvar = pd.Series(calories, index = ["day1", "day2"]) DataFrame.iat. Example. A Pandas Series is like a column in a table. ; dtypes for data types. In order to find the index-only values, you can use the index function along with the series name and in return you will get all the index values as well as datatype of the index. See also. DataFrame.loc. pandas.Index.values¶ property Index.values¶. pandas.Series.loc¶ property Series.loc¶. What is a Series? Series is a one-dimensional labeled array capable of holding data of any type (integer, string, float, python objects, etc.). ; index values. Example Access a group of rows and columns by label(s). A pandas Series can be created using the following constructor − pandas.Series( data, index, dtype, copy) The parameters of the constructor are as follows − An example is given below. In the below example we create a Series with a numeric index. For a Series with a MultiIndex, only remove the specified levels from the index. Allowed inputs are: A single label, e.g. The name to use for the column containing the original Series values. (Say index 2 => I need Japan) I used iloc, but i got the data (7.542) return countries.iloc[2] 7.542 Uses self.name by default. Removes all levels by default. The axis labels are collectively called index. It is a one-dimensional array holding data of any type. A panadas series is created by supplying data in various forms like ndarray, list, constants and the index values which must be unique and hashable. I have a Pandas dataframe (countries) and need to get specific index value. fruits.index. Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages and makes importing and analyzing data much easier.. Pandas str.index() method is used to search and return lowest index of a substring in particular section (Between start and end) of every string in a series. Creating Pandas Series. Return an array representing the data in the Index. Output: Index(['apple', 'banana', 'orange', 'pear', 'peach'], dtype='object') Above, you can see the data type of the index … Just reset the index, without inserting it as a column in the new DataFrame. Example – Series Get Value by Index. Let's first create a pandas series and then access it's elements. Then we are trying to get the second value from the Series using the index. pandas.Series. The elements of a pandas series can be accessed using various methods. Access a group of rows and columns by label(s) or a boolean array..loc[] is primarily label based, but may also be used with a boolean array. ; Copy data, default is False. Suppose we want to change the order of the index of series, then we have to use the Series.reindex() Method of pandas module for performing this task.. Series, which is a 1-D labeled array capable of holding any data.. Syntax: pandas.Series(data, index, dtype, copy) Parameters: data takes ndarrys, list, constants. The first one using an integer index and the second using a string based index. ['a', 'b', 'c']. Access a single value for a row/column pair by integer position. A list or array of labels, e.g. 5 or 'a', (note that 5 is interpreted as a label of the index, and never as an integer position along the index). If multiple values equal the maximum, the first row label with that value is … name: object, optional. pandas.Series.idxmax¶ Series.idxmax (axis = 0, skipna = True, * args, ** kwargs) [source] ¶ Return the row label of the maximum value. drop: bool, default False.