How do i print a column length in python?

This article describes how to get the number of rows, columns, and total number of elements [size] of pandas.DataFrame and pandas.Series.

• pandas.DataFrame
  • Display number of rows, columns, etc.: df.info[]
  • Get the number of rows: len[df]
  • Get the number of columns: len[df.columns]
  • Get the number of rows and columns: df.shape
  • Get the number of elements: df.size
  • Notes when specifying index
• pandas.Series
  • Get the number of elements: len[s], s.size

As an example, use Titanic survivor data. It can be downloaded from Kaggle.

import pandas as pd

df = pd.read_csv['data/src/titanic_train.csv']

print[df.head[]]
#    PassengerId  Survived  Pclass  \
# 0            1         0       3   
# 1            2         1       1   
# 2            3         1       3   
# 3            4         1       1   
# 4            5         0       3   
# 
#                                                 Name     Sex   Age  SibSp  \
# 0                            Braund, Mr. Owen Harris    male  22.0      1   
# 1  Cumings, Mrs. John Bradley [Florence Briggs Th...  female  38.0      1   
# 2                             Heikkinen, Miss. Laina  female  26.0      0   
# 3       Futrelle, Mrs. Jacques Heath [Lily May Peel]  female  35.0      1   
# 4                           Allen, Mr. William Henry    male  35.0      0   
# 
#    Parch            Ticket     Fare Cabin Embarked  
# 0      0         A/5 21171   7.2500   NaN        S  
# 1      0          PC 17599  71.2833   C85        C  
# 2      0  STON/O2. 3101282   7.9250   NaN        S  
# 3      0            113803  53.1000  C123        S  
# 4      0            373450   8.0500   NaN        S  

Get the number of rows, columns, elements of pandas.DataFrame

Display number of rows, columns, etc.: df.info[]

The info[] method of pandas.DataFrame can display information such as the number of rows and columns, the total memory usage, the data type of each column, and the number of non-NaN elements.

df.info[]
# 
# RangeIndex: 891 entries, 0 to 890
# Data columns [total 12 columns]:
# PassengerId    891 non-null int64
# Survived       891 non-null int64
# Pclass         891 non-null int64
# Name           891 non-null object
# Sex            891 non-null object
# Age            714 non-null float64
# SibSp          891 non-null int64
# Parch          891 non-null int64
# Ticket         891 non-null object
# Fare           891 non-null float64
# Cabin          204 non-null object
# Embarked       889 non-null object
# dtypes: float64[2], int64[5], object[5]
# memory usage: 83.6+ KB

The result is standard output and cannot be obtained as a value.

Get the number of rows: len[df]

The number of rows of pandas.DataFrame can be obtained with the Python built-in function len[].

In the example, it is displayed using print[], but len[] returns an integer value, so it can be assigned to another variable or used for calculation.

Get the number of columns: len[df.columns]

The number of columns of pandas.DataFrame can be obtained by applying len[] to the columns attribute.

print[len[df.columns]]
# 12

Get the number of rows and columns: df.shape

The shape attribute of pandas.DataFrame stores the number of rows and columns as a tuple [number of rows, number of columns].

print[df.shape]
# [891, 12]

print[df.shape[0]]
# 891

print[df.shape[1]]
# 12

It is also possible to unpack and store them in separate variables.

• Unpack a tuple and list in Python

row, col = df.shape
print[row]
# 891

print[col]
# 12

Get the number of elements: df.size

The total number of elements of pandas.DataFrame is stored in the size attribute. This is equal to the row_count * column_count.

print[df.size]
# 10692

print[df.shape[0] * df.shape[1]]
# 10692

Notes when specifying index

When a column of data is specified as an index by the set_index[] method, these columns are removed from the data body [values attribute], so it is not counted as the number of columns.

df_multiindex = df.set_index[['Sex', 'Pclass', 'Embarked', 'PassengerId']]

print[len[df_multiindex]]
# 891

print[len[df_multiindex.columns]]
# 8

print[df_multiindex.shape]
# [891, 8]

print[df_multiindex.size]
# 7128

See the following article for set_index[].

• pandas: Assign existing column to the DataFrame index with set_index[]

Get the number of elements of pandas.Series

As an example of pandas.Series, select one row from pandas.DataFrame.

s = df['PassengerId']
print[s.head[]]
# 0    1
# 1    2
# 2    3
# 3    4
# 4    5
# Name: PassengerId, dtype: int64

Get the number of elements : len[s], s.size

Since pandas.Series is one-dimensional, you can get the total number of elements [size] with either len[] or size attribute.

Note that the shape attribute is a tuple with one element.

print[len[s]]
# 891

print[s.size]
# 891

print[s.shape]
# [891,]

There is no info[] method in pandas.Series.

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