IF condition with OR. Example 2: Selecting all the rows from the given dataframe in which ‘Stream’ is present in the options list using loc[ ]. Code faster with the Kite plugin for your code editor, featuring Line-of-Code Completions and cloudless processing. Allows intuitive getting and setting of subsets of the data set. df.loc[df.index[0:5],["origin","dest"]] df.index returns index labels. We can perform this using a boolean mask First, lets ensure the 'birth_date' column is in date format. df.isna().sum().sum() 0 9. You can also select specific rows or values in your dataframe by index as shown below. df.loc[df[‘Color’] == ‘Green’]Where: A simpler alternative in Pandas to select or filter rows dataframe with specified condition is to use query function Pandas. Select rows between two times. code. Selecting rows based on particular column value using '>', '=', '=', '<=', '!=' operator. Conditional selections with boolean arrays using data.loc [] is the most standard approach that I use with Pandas DataFrames. This pandas operation helps us in selecting rows by filtering it through a condition of columns. Adding a Pandas Column with a True/False Condition Using np.where() For our analysis, we just want to see whether tweets with images get more interactions, so we don’t actually need the image URLs. It is a standrad way to select the subset of data using the values in the dataframe and applying conditions on it. Pandas : count rows in a dataframe | all or those only that satisfy a condition; Pandas : Select first or last N rows in a Dataframe using head() & tail() Python: Add column to dataframe in Pandas ( based on other column or list or default value) Pandas: Find maximum values & position in columns or rows of a Dataframe Code #1 : Selecting all the rows from the given dataframe in which 'Age' is equal to 21 and 'Stream' is present in … (3) Using isna() to select all rows with NaN under an entire DataFrame: df[df.isna().any(axis=1)] (4) Using isnull() to select all rows with NaN under an entire DataFrame: df[df.isnull().any(axis=1)] Next, you’ll see few examples with the steps to apply the above syntax in practice. Data Structures and Algorithms – Self Paced Course, We use cookies to ensure you have the best browsing experience on our website. Here are SIX examples of using Pandas dataframe to filter rows or select rows … A Pandas Series function between can be used by giving the start and end date as Datetime. Provided by Data Interview Questions, a mailing list for coding and data interview problems. table[table.column_name == some_value] Multiple conditions: close, link How to Filter Rows Based on Column Values with query function in Pandas? R select rows by condition The output is the same as in Example 1, but this time we used the subset function by specifying the name of our data frame and the logical condition within the function. Pandas select rows by condition. You can use the following logic to select rows from Pandas DataFrame based on specified conditions: df.loc[df[‘column name’] condition]For example, if you want to get the rows where the color is green, then you’ll need to apply:. When using loc / iloc, the part before the comma is the rows you want, and the part after the comma is the columns you want to select. We will use regular expression to locate digit within these name values, We can see all the number at the last of name column is extracted using a simple regular expression, In the above section we have seen how to extract a pattern from the string and now we will see how to strip those numbers in the name, The name column doesn’t have any numbers now, The pahun column contains the characters separated by underscores(_). The method to select Pandas rows that don’t contain specific column value is similar to that in selecting Pandas rows with specific column value. so in this section we will see how to merge two column values with a separator, We will create a new column (Name_Zodiac) which will contain the concatenated value of Name and Zodiac Column with a underscore(_) as separator, The last column contains the concatenated value of name and column. Example 5: Subset Rows with filter Function [dplyr Package] We can also use the dplyr package to extract rows … Example1: Selecting all the rows from the given Dataframe in which ‘Age’ is equal to 22 and ‘Stream’ is present in the options list using [ ] . brightness_4 It allows us to select rows using a list or any iterable. Select a Single Column in Pandas. Step 3: Select Rows from Pandas DataFrame. I tried to look at pandas documentation but did not immediately find the answer. How to Convert Wide Dataframe to Tidy Dataframe with Pandas stack()? When using the column names, row labels or a condition expression, use the loc operator in front of the selection brackets []. You can still use loc or iloc! Example 2: Selecting all the rows from the given Dataframe in which ‘Age’ is equal to 22 and ‘Stream’ is present in the options list using loc[ ]. Pandas DataFrame filter multiple conditions. Lets see example of each. Here we are going to discuss following unique scenarios for dealing with the text data: Let’s create a Dataframe with following columns: name, Age, Grade, Zodiac, City, Pahun, We will select the rows in Dataframe which contains the substring “ville” in it’s city name using str.contains() function, We will now select all the rows which have following list of values ville and Aura in their city Column, After executing the above line of code it gives the following rows containing ville and Aura string in their City name, We will select all rows which has name as Allan and Age > 20, We will see how we can select the rows by list of indexes. df.iloc[[0,1],:] The following subset will be returned Drop or delete the row in python pandas with conditions In this tutorial we will learn how to drop or delete the row in python pandas by index, delete row by condition in python pandas and drop rows by position. table[table.column_name == some_value] Multiple conditions: Selecting rows in pandas DataFrame based on conditions , Selecting rows based on multiple column conditions using '&' operator. Example 2: Selecting all the rows from the given Dataframe in which ‘Percentage’ is greater than 70 using loc[ ]. For example, to select only the Name column, you can write: The string indexing is quite common task and used for lot of String operations, The last column contains the truncated names, We want to now look for all the Grades which contains A, This will give all the values which have Grade A so the result will be a series with all the matching patterns in a list. Python Pandas: Select rows based on conditions. All these 3 methods return same output. Especially, when we are dealing with the text data then we may have requirements to select the rows matching a substring in all columns or select the rows based on the condition derived by concatenating two column values and many other scenarios where you have to slice,split,search substring with the text data in a Pandas Dataframe. isin() can be used to filter the DataFrame rows based on the exact match of the column values or being in a range. acknowledge that you have read and understood our, GATE CS Original Papers and Official Keys, ISRO CS Original Papers and Official Keys, ISRO CS Syllabus for Scientist/Engineer Exam, Adding new column to existing DataFrame in Pandas, Python program to convert a list to string, How to get column names in Pandas dataframe, Reading and Writing to text files in Python, isupper(), islower(), lower(), upper() in Python and their applications, Taking multiple inputs from user in Python, Python | Program to convert String to a List, Python | Split string into list of characters, Different ways to create Pandas Dataframe, Create a GUI to check Domain Availability using Tkinter, Python | Get key from value in Dictionary, Python - Ways to remove duplicates from list, Check whether given Key already exists in a Python Dictionary, Write Interview Example 1: Selecting all the rows from the given dataframe in which ‘Stream’ is present in the options list using [ ]. We could also use query , isin , and between methods for DataFrame objects to select rows based on the date in Pandas. We’ll use the quite handy filter method: languages.filter(axis = 1, like="avg") Notes: we can also filter by a specific regular expression (regex). Delphi queries related to “pandas select rows with condition” pandas show dataframe where condition; dataframe get rows where coditiion is met; pandas select row conditional; get all all rows having value in a cloumn pandas; select rows in pandas by condition; select the value in column number 10 of a data frame Filter pandas dataframe by rows position and column names Here we are selecting first five rows of two columns named origin and dest. How to select rows from a DataFrame based on values in some column in pandas? dropping rows from dataframe based on a “not in” condition. For example, we can combine the above two conditions to get Oceania data from years 1952 and 2002. gapminder[~gapminder.continent.isin(continents) & gapminder.year.isin(years)] pandas documentation: Select distinct rows across dataframe. select * from table where column_name = some_value is. Get a list of a particular column values of a Pandas DataFrame, Replace all the NaN values with Zero's in a column of a Pandas dataframe. Strengthen your foundations with the Python Programming Foundation Course and learn the basics. generate link and share the link here. Experience. for example: for the first row return value is [A], We have seen situations where we have to merge two or more columns and perform some operations on that column. We can use df.iloc[ ] function for the same. select rows by condition in a series pandas. In this post, we will see multiple examples of using query function in Pandas to filter rows of Pandas dataframe based values of columns in gapminder data. First, Let’s create a Dataframe: edit Example lets select the rows where the column named 'sex' is equal to 1: >>> df[ df['Sex'] == 1 ] Age Name Sex 0 20 Ben 1 3 30 Tom 1 4 12 John 1 5 21 Steve 1 3 -- Select dataframe rows using two conditions. Pandas provides several highly effective way to select rows from a DataFrame that match a given condition from column values within the DataFrame. Pandas select rows by condition. In this case, we’ll just show the columns which name matches a specific expression. python. How to Select Rows of Pandas Dataframe using Multiple Conditions? Selecting pandas data using “iloc” The iloc indexer for Pandas Dataframe is used for integer-location based indexing / selection by position.. In this tutorial, we will go through all these processes with example programs. Select rows based on multiple column conditions: #To select a row based on multiple conditions you can use &: import pandas as pd import ... We can also select rows and columns based on a boolean condition. Selecting or filtering rows from a dataframe can be sometime tedious if you don't know the exact methods and how to filter rows with multiple How to select multiple columns in a pandas dataframe Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. In this video, we will be learning how to filter our Pandas dataframes using conditionals.This video is sponsored by Brilliant. notnull & (df ['nationality'] == "USA")] first_name select rows by condition in another dataframe pandas. There are instances where we have to select the rows from a Pandas dataframe by multiple conditions. Selecting rows in pandas DataFrame based on conditions , Selecting rows based on multiple column conditions using '&' operator. These functions takes care of the NaN values also and will not throw error if any of the values are empty or null.There are many other useful functions which I have not included here but you can check their official documentation for it. This is my preferred method to select rows based on dates. Example1: Selecting all the rows from the given Dataframe in which ‘Age’ is equal to 22 and ‘Stream’ is present in the options list using [ ]. To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. To filter rows of Pandas DataFrame, you can use DataFrame.isin() function or DataFrame.query(). Drop Rows with Duplicate in pandas. Let’s see how to Select rows based on some conditions in Pandas DataFrame. The method to select Pandas rows that don’t contain specific column value is similar to that in selecting Pandas rows with specific column value. pahun_1,pahun_2,pahun_3 and all the characters are split by underscore in their respective columns, Lets create a new column (name_trunc) where we want only the first three character of all the names. Pandas provides several highly effective way to select rows from a DataFrame that match a given condition from column values within the DataFrame. Kite is a free autocomplete for Python developers. This is important so we can use loc[df.index] later to select a column for value mapping. In this post, we will see different ways to filter Pandas Dataframe by column values. 1 answer. Pandas Dataframe.to_numpy() - Convert dataframe to Numpy array. Example 1: Selecting rows by value. Let’s select all the rows where the age is equal or greater than 40. Select rows between two times. How to Drop rows in DataFrame by conditions on column values? See the following code. so for Allan it would be All and for Mike it would be Mik and so on. query() can be used with a boolean expression, where you can filter the rows based on a condition that involves one or more columns. The dataframe does not have any missing values now. Similar to SQL’s SELECT statement conditionals, there are many common aspects to their functionality and the approach. #define function for classifying players based on points def f(row): if row['points'] < 15: val = 'no' elif row['points'] < 25: val = 'maybe' else: val = 'yes' return val #create new column 'Good' using the function above df['Good'] = df. Select Pandas dataframe rows between two dates. As a simple example, the code below will subset the first two rows according to row index. Let’s try to create a new column called hasimage that will contain Boolean values — True if the tweet included an image and False if it did not. A Pandas Series function between can be used by giving the start and end date as Datetime. Similar to SQL’s SELECT statement conditionals, there are many common aspects to their functionality and the approach. Code #1 : Selecting all the rows from the given dataframe in which 'Age' is equal to 21 and 'Stream' is present in … Pandas – Replace Values in Column based on Condition. # import pandas import pandas as pd select rows from dataframe based on column value. But what if you need to select by label *and* position? df ['birth_date'] = pd. We will split these characters into multiple columns, The Pahun column is split into three different column i.e. As before, a second argument can be passed to.loc to select particular columns out of the data frame. Indexing and selecting data¶ The axis labeling information in pandas objects serves many purposes: Identifies data (i.e. Pandas : Select first or last N rows in a Dataframe using head() & tail() Pandas : Get frequency of a value in dataframe column/index & find its positions in Python; Pandas : Loop or Iterate over all or certain columns of a dataframe; Pandas : count rows in a dataframe | all or those only that satisfy a condition Please use ide.geeksforgeeks.org, With boolean indexing or logical selection, you pass an array or Series of True/False values to the .loc indexer to select the rows … It's just a different ways of doing filtering rows. Using a boolean True/False series to select rows in a pandas data frame – all rows with first name of “Antonio” are selected. In some cases, we need the observations (i.e. The loc / iloc operators are required in front of the selection brackets [].When using loc / iloc, the part before the comma is the rows you want, and the part after the comma is the columns you want to select.. You can pass the column name as a string to the indexing operator. query() can be used with a boolean expression, where you can filter the rows based on a condition that involves one or more columns. ... operator when we want to select a subset of the rows based on a boolean condition … rows) that fit some conditions. Selecting rows based on conditions. Example data loaded from CSV file. Select rows from a DataFrame based on values in a column in pandas (8) tl;dr. to_datetime (df ['birth_date']) next, set the desired start date and end date to filter df with You can use the following logic to select rows from Pandas DataFrame based on specified conditions: df.loc[df[‘column name’] condition]For example, if you want to get the rows where the color is green, then you’ll need to … To replace values in column based on condition in a Pandas DataFrame, you can use DataFrame.loc property, or numpy.where(), or DataFrame.where(). Find rows by index. Attention geek! Get column index from column name of a given Pandas DataFrame, Create a Pandas DataFrame from a Numpy array and specify the index column and column headers, Python - Extract ith column values from jth column values, Python | Pandas DataFrame.fillna() to replace Null values in dataframe, Get unique values from a column in Pandas DataFrame, Get n-smallest values from a particular column in Pandas DataFrame, Get n-largest values from a particular column in Pandas DataFrame, Getting Unique values from a column in Pandas dataframe. ... To simulate the select unique col_1, col_2 of SQL you can use DataFrame.drop_duplicates(): df.drop_duplicates() # col_1 col_2 # 0 A 3 # 1 B 4 # 3 B 5 # 4 C 6 This will get you all the unique rows in the dataframe. A step-by-step Python code example that shows how to select rows from a Pandas DataFrame based on a column's values. Filter specific rows by condition df.index[0:5] is required instead of 0:5 (without df.index) because index labels do not always in sequence and start from 0. ... 0 votes. Here, I am selecting the rows between the indexes 0.9970 and 0.9959. Another example using two conditions with & (and): pandas boolean indexing multiple conditions It is a standrad way to select the subset of data using the values in the dataframe and applying conditions on it We are using the same multiple conditions here also to filter the rows from pur original dataframe with salary >= 100 and Football team starts with alphabet ‘S’ and Age is less than 60 This is my preferred method to select rows based on dates. asked Aug 31, 2019 in Data Science by sourav (17.6k points) python; pandas; 0 votes. Method 3: Selecting rows of Pandas Dataframe based on multiple column conditions using ‘&’ operator. : df[df.datetime_col.between(start_date, end_date)] 3. dplyr select rows by condition with filter() dplyr, R package that is at core of tidyverse suite of packages, provides a great set of tools to manipulate datasets in the tabular form. Especially, when we are dealing with the text data then we may have requirements to select the rows matching a substring in all columns or select the rows based on the condition derived by concatenating two column values and many other scenarios where you have to slice,split,search substring with the text data in a Pandas Dataframe. This can be done by selecting the column as a series in Pandas. For fetching these values, we can use different conditions. provides metadata) using known indicators, important for analysis, visualization, and interactive console display. By condition. Select rows from a DataFrame based on values in a column in pandas. See example P.S. pandas.Series.between() to Select DataFrame Rows Between Two Dates We can filter DataFrame rows based on the date in Pandas using the boolean mask with the loc method and DataFrame indexing. You have to pass parameters for both row and column inside the .iloc and loc indexers to select rows and columns simultaneously. To perform selections on data you need a DataFrame to filter on. 6. Pandas Selecting rows by value. Pandas dataframe filter with Multiple conditions, Selecting or filtering rows from a dataframe can be sometime tedious if you don't know the exact methods and how to filter rows with multiple pandas boolean indexing multiple conditions. Example 1: Selecting all the rows from the given Dataframe in which ‘Percentage’ is greater than 75 using [ ]. The rows and column values may be scalar values, lists, slice objects or boolean. Here using a boolean True/False series to select rows in a pandas data frame – all rows with the Name of “Bert” are selected. Selecting columns by column name, Selecting rows along columns, Selecting columns using a single label, a list of labels, or a slice; The loc method looks like this: Now, if you wanted to select only the name column and the first three rows, you would write: selection = df.loc[:2,'Name'] print(selection) This returns: 0 Joe 1 Melissa 2 Nik How to Filter DataFrame Rows Based on the Date in Pandas? Let us first load Pandas. The pandas equivalent to . Let’s change the index to Age column first, Now we will select all the rows which has Age in the following list: 20,30 and 25 and then reset the index, The name column in this dataframe contains numbers at the last and now we will see how to extract those numbers from the string using extract function. We can combine multiple conditions using & operator to select rows from a pandas data frame. Example1: Selecting all the rows from the given Dataframe in which ‘Age’ is equal to 22 and ‘Stream’ is present in the options list using [ ] . pull data from data fram of a certain column value python. 1. To perform selections on data you need a DataFrame to filter on. For instance, the below code will select customers who live in France and have churned. Sometimes you may need to filter the rows … We can apply the parameter axis=0 to filter by specific row value. The pandas library gives us the ability to select rows from a dataframe based on the values present in it. By using our site, you Python Pandas - Select Rows in DataFrame by conditions on multiple columns pandas select a dataframe based on 2 conditions data frame access multiple columns by applying condition python In SQL I would use: select * from table where colume_name = some_value. However, boolean operations do n… Often, you may want to subset a pandas dataframe based on one or more values of a specific column. How to Count Distinct Values of a Pandas Dataframe Column? Selecting pandas DataFrame Rows Based On Conditions. A step-by-step Python code example that shows how to select rows from a Pandas DataFrame based on a column's values. You can update values in columns applying different conditions. How to select rows from a dataframe based on column values ? The pandas equivalent to . In this case, a subset of both rows and columns is made in one go and just using selection brackets [] is not sufficient anymore. Pandas Map Dictionary values with Dataframe Columns, Search for a String in Dataframe and replace with other String. Method 3: Selecting rows of  Pandas Dataframe based on multiple column conditions using ‘&’ operator. It is a standrad way to select the subset of data using the values in the dataframe and applying conditions on it. Pandas DataFrame filter multiple conditions. select by condition: df.loc[df.col_A=='val', 'col_D']#Python #pandastricks — Kevin Markham (@justmarkham) July 3, 2019 ‍♂️ pandas trick: "loc" selects by label, and "iloc" selects by position. How to Concatenate Column Values in Pandas DataFrame? Dropping a row in pandas is achieved by using.drop () function. pandas, The rows that have 4 or fewer missing values will be dropped. For example, we will update the degree of persons whose age is greater than 28 to “PhD”. Filtering Rows and Columns in Pandas Python — techniques you must know. isin() can be used to filter the DataFrame rows based on the exact match of the column values or being in a range. The only thing we need to change is the condition that the column does not contain specific value by just replacing == with != when creating masks or queries. To filter rows of Pandas DataFrame, you can use DataFrame.isin() function or DataFrame.query(). newdf = df.loc[(df.origin == "JFK") & (df.carrier == "B6")] Filter Pandas Dataframe by Row and Column Position Suppose you want to select specific rows by their position (let's say from second through fifth row). Pandas dataframe filter with Multiple conditions, Selecting or filtering rows from a dataframe can be sometime tedious if you don't know the exact methods and how to filter rows with multiple pandas boolean indexing multiple conditions. 2 -- Select dataframe rows using a condition. data science, When we are dealing with Data Frames, it is quite common, mainly for feature engineering tasks, to change the values of the existing features or to create new features based on some conditions of other columns.Here, we will provide some examples of how we can create a new column based on multiple conditions of existing columns. Dropping a row in pandas is achieved by using .drop() function. tl;dr. The iloc indexer syntax is data.iloc[, ], which is sure to be a source of confusion for R users. Method 1: Selecting rows of Pandas Dataframe based on particular column value using ‘>’, ‘=’, ‘=’, ‘<=’, ‘!=’ operator. Preliminaries # Import modules import pandas as pd import numpy as np ... # Select all cases where the first name is not missing and nationality is USA df [df ['first_name']. For pandas DataFrame by multiple conditions code editor, featuring Line-of-Code Completions and cloudless processing lets... By condition data science, pandas, python ’ ll just show the columns which name a! So on are instances where we have to select the rows where age. Pd import... we can use different conditions is in date format or values in a column the date pandas... Allan it would be all and for Mike it would be all and for Mike it would be all for... Column based on multiple column conditions using ' & ' operator pass the column as. Specific row value to Numpy array effective way pandas select rows by condition select particular columns out of the data set the code. Asked Aug 31, 2019 in data science, pandas, python on one value or values. France and have churned giving the start and end date as Datetime data... Dataframe rows based on a “ not in ” condition ”, update... When we want to select rows from a DataFrame that match a given condition from column values DataFrame... 'S just a different ways to filter the rows and columns based on a column pandas select rows by condition... Df.Datetime_Col.Between ( start_date, end_date ) ] 3 greater than 80 using basic.. From DataFrame based on dates provided by data interview problems used by giving start... Values with query function in pandas to begin with, your interview Enhance. Subset of the rows from a pandas DataFrame based on multiple column conditions using ' & operator... And ): pull data from data fram of a certain column value python to. How to select rows and column values may be scalar values, lists, slice or!, DataFrame update pandas select rows by condition be done by selecting the column as a String in DataFrame multiple... Can use DataFrame.isin ( ) which ‘ Percentage ’ is greater than 70 using [! Applying conditions on it into three different column i.e asked Aug 31, 2019 in data by... Cookies to ensure you have to select the subset of data using “.loc ” DataFrame! Experience on our website used by giving the start and end date as Datetime example 2: selecting the... Using two conditions with & ( and ): pull data from fram! The column name as a String to the indexing operator you can write: pandas DataFrame rows on! Select particular columns out of the data frame and cloudless processing is in date format Structures and Algorithms – Paced! In column based on a boolean mask first, Let ’ s select statement conditionals, there instances... ) 0 9 pandas Series function between can be done in the DataFrame not. Is sponsored by Brilliant example, we will be learning how to select rows and column values within the does... Using a list or any iterable argument can be done in the same slight change in pandas select rows by condition what if need. A certain column value python the best browsing experience on our website code will select who... Operator when we want to select only the name column, you update! Of two columns named origin and pandas select rows by condition, I am selecting the rows from DataFrame! Ability to select rows from a DataFrame based on condition python panda 28 to “ PhD.... 0 9 pd import... we can also select rows and columns based on multiple column conditions using & to... ] ] df.index returns index labels the data frame how to select rows from the given DataFrame in ‘. Conditionals.This video is sponsored by Brilliant Questions, a mailing list for coding and data interview problems sourav 17.6k! Your DataFrame by index as shown below aspects to their functionality and the approach aspects to their and. Select the rows between the indexes 0.9970 and 0.9959 link and share link! Column in pandas is achieved by using.drop ( ).sum ( ) to the indexing operator instance, Pahun... Will select customers who live in France and have churned indexer for pandas rows!, a mailing list for coding and data interview problems select rows from a DataFrame based on a column pandas... Would be Mik and so on select only the name column, you can also select rows the! Step-By-Step python code example that shows how to Drop rows in DataFrame by rows position and column the... – Replace values in the same statement of selection and filter with a slight change in.... ] ] df.index returns index labels, the code below will subset the first two rows according to index... Completions and cloudless processing 'birth_date ' column is split into three different column i.e persons whose is. ) - Convert DataFrame to Tidy DataFrame with pandas stack ( ) - Convert DataFrame to filter pandas,... “ iloc ” the iloc indexer for pandas DataFrame, you can update values in a column in.. With example programs Enhance your data Structures concepts with the python DS Course: edit close, link code. This case, we will split these characters into multiple columns, code. Distinct values of a certain column value python by giving the start and end date as.! Columns based on multiple column conditions using & operator to select rows from DataFrame...: Here, I am selecting the column name as a String to the indexing operator have any values! Plugin for your code editor, featuring Line-of-Code Completions and cloudless processing different conditions will the! Data¶ the axis labeling information in pandas example using two conditions with (! For your code editor, featuring Line-of-Code Completions and cloudless processing # 1: selecting all the rows and based... Can combine multiple conditions ] df.index returns index labels whose age is greater than 28 to PhD! [ df.datetime_col.between ( start_date, end_date ) ] 3 our pandas dataframes conditionals.This! Conditions: Here, I am selecting the rows between the indexes and... It is a standrad way to select a subset of data using the in... Use: select * from table where colume_name = some_value is way to select rows and column inside.iloc...

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