## removing sequences from the data Pandas Python Numpy

pandas drop rows with condition

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pandas iloc

drop first row pandas

drop multiple rows pandas

pandas drop index

I have tried the following:

>>> import pandas as pd >>> import numpy as np >>> df = pd.read_csv("training.csv") >>> data_raw = df.values >>> data = [] >>> seq_len = 5 >>> for index in range(len(data_raw) - seq_len): ... data.append(data_raw[index: index + seq_len]) ... >>> len(data) 1994 >>> len(data_raw) 1999 >>> del data[0]

The data is available here: training.csv
I have seen that the `del`

removes the first element from the array. And rearrange the values like what was on 1st position, is now the 0th position, and so on.
I want to remove the values at indices: `0,4,5,9,10,14,`

and so on.
But this is not getting possible with the current `del`

statement as it will rearrange the values.
Please help me find the missing part.

To start with, desired removal indices: `0,4,5,9,10,14,15,19,20,24,25,29...`

can be generated:

indices = [] for i in range(1,401): indices.append(5*(i-1)) indices.append(5*i-1) del indices[-1] # This is to remove 1999, which is out of index for df print(indices[:12]) [0, 4, 5, 9, 10, 14, 15, 19, 20, 24, 25, 29]

Then using `np.delete`

:

data_raw = np.random.randint(0, 10, size=(1999, 10)) new_data = np.delete(data_raw, indices, axis=0) # Since this is not inplace op

Validation:

np.array_equal(new_data[:6],data_raw[[1,2,3,6,7,8]]) # Where 0,4,5,9 is removed # True

**pandas: Delete rows, columns from DataFrame with drop(),** DataFrame.drop — pandas 0.21.1 documentation Here, the following If no row name is set, by default index will be a sequence of integers. The data frame data looks like this: pid tag 1 23 1 45 1 62 2 24 2 45 3 34 3 25 3 62 Now I count the number of tag occurrences like this: bytag = data.groupby('tag').aggregate(np.count_nonzero) But then I can't figure out how to remove those entries which have low count

you can do it like this

**example code:**

index = [0,4,5,9,10,14] for i, x in enumerate(index): index[i] -= i print(index) for i in index: del data[i]

**How to drop one or multiple columns from Pandas Dataframe,** To make use of any python library, we first need to load them up by using import command. import pandas as pd import numpy as np. Let's create� Python for Data Analysis by Wes McKinney, the creator of Pandas Pandas Cookbook by Ted Petrou, a data science trainer and consultant Free Bonus: Click here to get access to a free NumPy Resources Guide that points you to the best tutorials, videos, and books for improving your NumPy skills.

Here's a simple way to overcome this:

a = list(range(10)) remove = [0,4,5]

Say you want to remove the indices in `remove`

from `a`

. What you can do is sort the elements in `remove`

in reverse order, and then remove them from `a`

in a for loop as:

for i in sorted(remove, reverse=True): del a[i]

** Output **

[1, 2, 3, 6, 7, 8, 9]

**The Pandas DataFrame: Make Working With Data Delightful – Real ,** Pandas DataFrame Labels as Sequences; Data as NumPy Arrays; Data Calculating With Missing Data; Filling Missing Data; Deleting Rows� arr = np.array ( [4, 5, 6, 7, 8, 9, 10, 11, 4, 5, 6, 33, 6, 7]) arr = np.array ( [4, 5, 6, 7, 8, 9, 10, 11, 4, 5, 6, 33, 6, 7]) Now let’s delete all occurrences of 6 from the above numpy array using np.argwhere () & np.delete () i.e. # Single line solution to delete all occurrences of element with value 6.

another way to do that

a = list(range(10)) print(a) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] to_drop = [0,4,5,9] #indices to drop values = [a[i] for i in to_drop] # values corresponding to the indices new_v = [a.remove(v) for v in values] # new list after dropping the values

**Output**

[1, 2, 3, 6, 7, 8]

I mean remove = [0,4,5,9], this should be the sequence in the remove list if the array is or 10 values. How I can create it dynamically?

This is for 100 values of array. Generated the indices where it needs to be dropped for batch size of 10. Do correct me if I have interpreted wrongly

to_drop = [[j+(i*10) for j in [0,4,5,9]] for i in range(10)]

O/P

[[0, 4, 5, 9], [10, 14, 15, 19], [20, 24, 25, 29], [30, 34, 35, 39], [40, 44, 45, 49], [50, 54, 55, 59], [60, 64, 65, 69], [70, 74, 75, 79], [80, 84, 85, 89], [90, 94, 95, 99]]

**Indexing and Selecting Data — pandas 0.13.1 documentation,** The Python and NumPy indexing operators [] and attribute operator . provide the original DataFrame, with True wherever the element is in the sequence of values. Slightly nicer by removing the parentheses (by binding making comparison� Data as NumPy Arrays. Sometimes you might want to extract data from a Pandas DataFrame without its labels. To get a NumPy array with the unlabeled data, you can use either .to_numpy() or .values: >>>

**pandas.DataFrame — pandas 0.18.1 documentation,** data : numpy ndarray (structured or homogeneous), dict, or DataFrame dicts of Series, arrays, or dicts; DataFrame.from_items: from sequence of (key, value) pairs **kwargs), Return DataFrame with duplicate rows removed, optionally only. DataFrame.dropna () Python’s pandas library provides a function to remove rows or columns from a dataframe which contain missing values or NaN i.e. DataFrame.dropna(self, axis=0, how='any', thresh=None, subset=None, inplace=False)

**Indexing and selecting data — pandas 0.8.1 documentation,** Similar to numpy ndarrays, pandas Index, Series, and DataFrame also If you want to identify and remove duplicate rows in a DataFrame, there are two Sometimes you want to extract a set of values given a sequence of row labels and� Python | Delete rows/columns from DataFrame using Pandas.drop() 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.DataFrame.reset_index — pandas 1.0.5 documentation,** pandas.DataFrame.reset_index�. DataFrame. reset_index (self, level: Union[ Hashable, Sequence[Hashable], NoneType] = None, drop: bool = False, inplace: � Although lists, NumPy arrays, and Pandas dataframes can all be used to hold a sequence of data, these data structures are built for different purposes. Lists are simple Python built-in data structures, which can be easily used as a container to hold a dynamically changing data sequence of different data types, including integer, float, and object.

##### Comments

- If you don't want to change your list size, you should replace the deleted indices with a constant value, Am I right?
- What is your rule of generating indices? is it
`5(n-1)`

and`5n - 1`

? - @Chris actually that is becoming a mystery for me :P. the sequence I found a pattern was like this
`0,4,5,9,10,14,15,19,20,24,25,29`

and so on. I am unable to figure it out whether what formula the pattern resembles. - @JafferWilson Gotcha. I'll upload a post accordingly.
- Thank you everyone for the answers. It was amazing.
- No sir, what you have suggested will edit the dataframe and not the array. I want the sequence from array to get removed and not from the dataframe. Do not want to disturb original frames.
- i was thinking like you first remove and the do
`df.values`

to get the array. - do you want to preserve the initial dataframe?
- No sir. Not from the dataframes. I want the sequence from array to get removed. Do you wanna say that it will be the same then I guess you are wrong.
- I do not want to copy a dataframe. as it will be safe if I operate on the arrays only and not the dataframe level
- Sir is there a way I create the sequence list to be removed till the data range. Say I have 10 elements, so how I can create the
`remove`

list till the array range? - You mean how can you modify
`remove`

so that no elements are greater than the length of`a`

? - Yes, sir. I mean if I need to create the array on my own, because data can be huge and need the sequence to be remove. Can you help me.
- No sir, I mean
`remove = [0,4,5,9]`

, this should be the sequence in the remove list if the array is or`10`

values. How I can create it dynamically? because imagine sir I have array of 100, how I manually can create the remove list? Please sir can you add that part in the answer it will be great. - But I don't understand what crietria you are following to create the sequence
`remove`

?